Ex-OpenAI engineer Daniel Levy and former Y Combinator partner Daniel Gross worked with Sutskever to cofound SSI together. In its release, SSI said, “Building safe superintelligence (SSI) is the most important technical problem of our time.” It said that the company’s investors and business model are aligned to achieve safe superintelligence.

The release added, “We approach safety and capabilities in tandem, as technical problems to be solved through revolutionary engineering and scientific breakthroughs. We plan to advance capabilities as fast as possible while making sure our safety always remains ahead.”

https://Twitter.com/ilyasut/status/1803472979873128498

Safety Concerns Over AI

Sutskever and many other AI critics have multiple genuine concerns amid the advancements of AI. It threatens to harm privacy in the short term and, in the long term, it could take over the world. The privacy fears were well illustrated when Microsoft revealed its new “Recall” feature for Copilot+ PCs at its Build conference event last month. The feature will record essentially everything you do on your PC to enable it to retrieve snapshots for you, enabling a potentially massive breach of privacy. After much online furor, Microsoft announced that it won’t be a default feature on the device.

Apple perhaps learned from that saga and, at the Worldwide Developer Conference earlier this month, said that safety would be the core of Apple Intelligence, even as it delivers personalized experiences. Apple Intelligence would run on several large language models (LLMs) many of which would run on the device itself.

According to SSI, “Our singular focus means no distraction by management overhead or product cycles, and our business model means safety, security, and progress are all insulated from short-term commercial pressures.”

https://Twitter.com/theuploadweekly/status/1803713121791410336

SSI It Putting a Lot of Focus on Safety

While Sutskever hasn’t revealed the company’s investors and financial backers, speaking with Bloomberg's Ashlee Vance he said that the company “will be fully insulated from the outside pressures of having to deal with a large and complicated product and having to be stuck in a competitive rat race.”

Meanwhile, it remains to be seen how the company advances in AI while not getting “distracted” by commercial pressures as investors have been quite demanding of the companies.

OpenAI Also Started as a Non-Profit AI Company

Incidentally, even OpenAI also started as a nonprofit but later became a for-profit company as it received billions of dollars in investments, including from Microsoft.

Elon Musk – another OpenAI confounder – has criticized OpenAI for transforming from a non-profit company to a “maximum profit” company. He has good reason to be upset as he donated tens of millions of dollars before it shifted to a non-profit (meaning that he got absolutely nothing for his money).

The billionaire has since disassociated himself from OpenAI and has started his own AI company X.ai which incidentally raised $6 billion late last month which gave the OpenAI competitor a valuation of a mammoth $24 billion.

https://www.youtube.com/watch?v=iGVRQBg43qM

Sutskever Backed Sam Altman’s Sacking

Sutskever was among those who backed Sam Altman’s sacking as OpenAI’s CEO. This mistake quickly turned into a tornado of controversy and chaos as most OpenAI employees threatened to quit if Altman wasn’t reinstated. In just a few days, Altman was brought back as CEO and Sutskever apologized for participating in the board’s action to remove him.

However, his position at OpenAI apparently became untenable after the incident. Meanwhile, the timing of his departure raised eyebrows, as it came just a day after OpenAI launched a new AI model along with a desktop version of ChatGPT.

Now with Sutskever starting his own AI company, the competition could heat up as SSI seems to put “safety” and “security” as its USPs at a time when individuals, institutions, as well as governments are getting wary of the emerging technology.

The post Will OpenAI Cofounder Ilya Sutskever’s New Safe AI Company Take Over the World? appeared first on Business2Community.

A record number of S&P 500 companies are discussing AI in their earnings calls, showing the excitement around the technology. However, Apple’s AI efforts have fallen short, and investors are aware. The iPhone maker has only risen about 5% this year and is lagging behind the Nasdaq index.

Nvidia, on the other hand, has raced ahead and is up over 150% in 2024, riding the AI wave. Yesterday, Nvidia surpassed Apple to become the world’s second-largest company as its market cap surpassed $3 trillion.

Apple Lost Its $3 Trillion Market Cap

Apple previously lost its $3 trillion market cap and the crown of the world’s biggest company to Microsoft. While its market cap hit $3 trillion again yesterday, it is now only the third biggest company globally. Apple investors are hoping that this WWDC could help it reclaim its former glory as the world's largest company.

Expectations from WWDC this year are elevated as Apple has teased AI-related announcements at the event. During the company’s fiscal Q2 earnings call, Apple CEO Tim Cook said, “We continue to feel very bullish about our opportunity in generative AI. We are making significant investments, and we're looking forward to sharing some very exciting things with our customers soon,” which was likely a reference to WWDC.

https://Twitter.com/MarioNawfal/status/1798334781953909226

What Are Markets Expecting from WWDC?

According to a report by Mac Rumors, Apple might make some key announcements at the event. It cited, Bloomberg's Apple afficianado Mark Gurman, who believes the iOS 18 will have a "relatively groundbreaking" software update with "major new features and designs," that would predominantly be focused on AI.

According to the publication, Apple is rumored to integrate AI into iOS with the following features:

• AI-assisted slide deck creation in Keynote
• Transcriptions for voice memos
• Generative AI functions in Safari web search
• Functionality to retouch photos with AI including a cleanup feature to remove objects
• AI-assisted writing in Pages and slide deck creation in Keynote
• Suggestions on replies to emails and messages
• Support for AI-generated custom emojis
• A smart recap of missed notifications
• AI-generated Apple Music playlists

Notably, Apple’s competitors have already come up with some of these features. Spotify for instance introduced an AI playlist builder in April. The feature will help users curate a personalized playlist based on the artists, tracks, and genres that AI would recommend.

Bloomberg recently reported that Apple is partnering with OpenAI to bring ChatGPT to its operating system and the fruits of this partnership could be announced at the WWDC. It could be a massive win-win deal as it empower millions of iPhone users with advanced AI while ChatGPT would secure a gargantuan user base.

Why are AI Product Enhancements Key for Apple?

Apple has been battling several challenges and the company's sales growth has been sluggish for the last many quarters. Its revenues fell YoY in all four quarters in the last fiscal year amid the slowdown in iPhone sales. In particular, it is facing tough competition in China where Huawei's smartphones have been a hit among consumers.

Apple’s Services business is also facing regulatory heat over the alleged monopolies in the App Store. While Apple and Alphabet maintain that they are not creating monopolies, users have few options to bypass the hefty fees that they charge on in-app purchases,

Amid rising competition, Apple has to step up its game and needs to make its devices AI-enabled to maintain its status as a premium smartphone company. Otherwise, the company risks falling behind other tech companies that have started to capitalize on AI.

https://www.youtube.com/watch?v=7eKK1QIpIPk

How do Analysts see AAPL Stock Ahead of WWDC?

2024 hasn’t been a good year for Apple, and the stock is among the worst-performing Big Tech companies with the notable exception of Tesla. The iPhone maker faced downgrades from three analysts in January which was quite rare for the company.

However, of late brokerages are turning bullish on Apple as it pivots to AI. JPMorgan analyst Samik Chatterjee is among those who believe AI products would help Apple spur hardware sales.

"The increasing appetite from investors has largely been driven by interest in participating in the cyclical upsides associated with the AI on-device led upgrade cycle, with investors taking the cue from the 5G-led upgrade cycle,” said Chatterjee in his note in April.

Dan Ives of Wedbush Securities also recently raised Apple’s target price to $275 as he predicts an iPhone supercycle.

Bank of America analyst Wamsi Mohan listed Apple as a top pick while maintaining a $230 target price. He said, “We view the upcoming AI enabled phones (IntelliPhones) to drive a multi-year upgrade cycle similar to the step function improvement driven by the introduction of smartphones.”

Mohan added, “With an installed base of over 4bn smartphones, we see the opportunity for the next upgrade cycle to be once in a decade type of event.”

https://Twitter.com/Machine4lpha/status/1765378953668137182

Can AAPL Reclaim Its Lost Glory?

While other Big Tech companies have seen a rerating amid the AI pivot, Apple’s efforts have lagged so far. Notably, tech companies have talked about their AI endeavors at length during their earnings calls over the last year, but the topic barely featured in Apple’s earnings calls.

The iPhone maker did a course correction and its Cook finally used the “golden words” during the fiscal Q1 earnings call earlier this year while teasing more announcements later in the year.

As Apple prepares for the WWDC, markets will closely watch the announcements this time around, especially on how the company plans to incorporate AI features in its devices. To reclaim its lost glory and the status as the world’s biggest company Apple needs to convince markets that it is pretty much in the AI race and not slacking in its efforts to offer AI features in its gadgets.

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The latest blow came after Tesla's Q4 2023 earnings release in late January, which showed decelerating sales and profit growth compared to recent blockbuster years. Shares plummeted over 12% the following day, wiping out around $80 billion in market capitalization in a stark reversal for the company once deemed the world's most valuable automaker.

While Tesla (TSLA) still reported a 38% year-over-year increase in vehicle deliveries for 2023, handing over 1.8 million cars to customers, the figure fell well short of its previous 50% annual growth targets that captivated investors and fueled an epic stock run-up.

More worryingly, the management team warned that growth in 2024 "may be notably lower" than last year as the company prioritizes the development of a new and more affordable "next-generation" vehicle platform that is expected to launch in the second half of 2025.

Missed Earnings and Rising Costs Spook Investors

Disappointing Q4 earnings figures also rattled Tesla’s bullish narratives regarding its profitability and pricing power. Adjusted earnings per share sank 40% from a year earlier, while revenue of $25.1 billion came in about $500 million below expectations despite recent deep price cuts.

Tesla's operating margin nearly halved year-over-year to just 8.2%, driven partly by rising costs associated with the launch of its polarizing Cybertruck pickup that went into production late last year.

Also read: Will Tesla Ever Reclaim Its Former Glory? Wave of Downgrades Hits the Stock Hard

Meanwhile, during the company's Q4 earnings call, the firm’s controversial CEO, Elon Musk, downplayed the prospect of a quick margin rebound, citing high interest rates as one of the factors pressuring prospective buyers.

"If the interest rates come down quickly, I think margins will be good. And if they don't come down quickly, they won't be that good", Musk told analysts. Unfortunately for Musk and Tesla, this is unlikely as the Federal Reserve is signaling caution as the market predicts the first rate cuts to be at least a few months away.

Analysts were highly critical of the lack of strategic vision and financial guidance provided on the call.

https://twitter.com/DivesTech/status/1750578723055644752?s=20

"We were dead wrong expecting Musk and team to step up like adults in the room on the call and give a strategic and financial overview of the ongoing price cuts, margin structure, and fluctuating demand", wrote Dan Ives of Wedbush Securities in a scathing note.

Rising Threat from China Pressures Demand Outlook

Musk himself highlighted the existential threat that Tesla now faces from rapidly ascending Chinese automakers like BYD, which overtook Tesla for the first time as the world's biggest seller of EVs and hybrids in Q4.

"Frankly, I think if there are not trade barriers established, [Chinese automakers] will pretty much demolish most other car companies in the world", Musk warned during the earnings conference.

His candid comments foreshadowed a looming potential showdown, as European officials have since launched an anti-dumping probe into Chinese EV exports that could lead to higher tariffs if the region determines unfair pricing practices.

The Next Battleground: Affordability

After years of working hard to become a dominant force in the nascent electric vehicles market, Tesla saw its stock valuation rise to lofty levels by achieving promising industry-leading profitability rather than growing at all costs – a strategy followed by most startups in the tech space.

Now, aftermarket conditions have shifted, the company appears to be resolved to pivot squarely toward affordability and cost-cutting – two flagship moves characteristic of Chinese automakers.

"Our key takeaway from the Tesla earnings call was the firm's strategic shift to the development and ramp-up of the new affordable sport utility vehicle, while focusing on cost cuts for its existing vehicles." wrote Seth Goldstein, senior equity analyst at Morningstar.

"This marks a change from the 2023 strategy, which was to cut prices to generate strong volume growth."

Goldstein expects to see a deceleration in Tesla's number of delivered vehicles to 10% in 2024 and 6% in 2025 as it prioritizes the development of its new affordable model line and keeps ramping up its Cybertruck output. Meanwhile, he forecasts that growth could be reignited to over 20% annually from 2026 onward, fueled by these affordable vehicles.

On the profitability front, Goldstein projects that automotive gross margins will remain depressed at around 19% over the next few years before rebounding as the lower-cost lineup achieves scale in the latter part of the decade.

Tesla Stock Valuation Has Been Reset After Years of Hype

If this profitability outlook holds true, it could mark a rude awakening for investors who bid up Tesla to nosebleed valuations based on the company's premium pricing power and sky-high growth ambitions.

At its 2021 peak of around $414 per share (post-split), Tesla shares traded at over 20 times projected 2030 sales, reflecting immense optimism that the company could maintain both its rapid growth and stellar profit margins well into the future. The reality is that the stock is now standing at around $175 per share or 58% below that mark. It turns out that the competition was able to catch up with Tesla much faster than expected.

"Tesla is signaling that the days of 50% or even 30% to 40% growth year-over-year is not going to happen in 2024", Goldstein told Bloomberg after the earnings release.

He cut his fair value estimate for Tesla shares to $200, still above current trading levels but a far cry from its heights just two years ago. Other analysts have also slashed their price targets, with Barclays lowering its projection to $225, down from $250, its previous forecast for the automaker.

Zooming Out: The Rise and Fall of Highflying Valuations

Tesla's valuation reset resembles similar moves suffered by other recently hyped-up stocks whose underlying business models were forced to confront harsher economic realities after years of exaggerated expectations.

The video conferencing company Zoom (ZM), for instance, became a household name during the remote work boom of the pandemic era. Nearly everyone, from students to workers to grandparents, all started using the app to connect with others online. The company’s stock price increased by over 300% in 2020 alone as revenues skyrocketed.

However, by late 2022, with offices reopening and competitive pressures intensifying, Zoom's shares have already given up nearly 89% of their value compared to their pandemic peak of $590 per share.

Meanwhile, the cloud data analytics firm Palantir experienced similar euphoria and subsequent reversal, riding the wave of COVID-era digital acceleration to see its shares quadruple from its direct listing in late 2020 through early 2021.

Although the AI boom has helped Palantir stock recover some of that lost territory, the price is still sitting far below its peak of $45 per share booked in 2021. In this particular case, the tailwinds that once lifted the company’s stock valuations have changed entirely. This has cushioned the blow but not yet totally reversed those post-pandemic.

Can Tesla Be Ousted from the ‘Magnificent 7’? This Professor Thinks So

For Jeremy Siegel, the legendary professor of finance emeritus at the University of Pennsylvania's Wharton School, the revaluation of Tesla and other recent market darlings is a positive sign for overall market health.

"There's more talk of a Magnificent 6 rather than 7 — highlighting Tesla's underperformance over last nine months or so.", Siegel wrote in a recent note, referring to the seven elite group of big tech stocks that has dominated market returns for a while.

"This is a sign of market health; the Magnificent 7 are not being treated all as one group and we see separation between Tesla and the others based on different earnings projections.", he further commented.

Looking Ahead: The Fallout for Musk?

Aside from the investor fallout, Tesla's humbling may carry major ramifications for its eccentric CEO as well.

Musk is reportedly seeking to increase his personal ownership stake in Tesla to around 25% from its current 13% level, ostensibly to exert more control and potentially pivot the company toward his growing interests in artificial intelligence and robotics.

The proposal has been met with skepticism by much of Wall Street, with analysts fearing that such a move would further distract Musk from righting the ship, referring to Tesla's core automotive business.

"If Musk does not get what he wants, will he leave Tesla?", pondered Peter Cohan, a Senior Contributor to Forbes. "Will he sell the company to a rival more interested in competing in the EV market?", he further reflexed.

The recent deterioration in Tesla’s business performance and the stock’s dramatic slide in 2024 undercuts Musk's leverage in such intra-company negotiations and raises the stakes over his ability to quickly refocus on delivering results on Tesla's primary mission.

If the pivot toward affordability hits roadblocks of its own, Musk may be forced to choose between following his AI side quest or devoting his full energy and ownership stake to the all-electric vehicle trailblazer he founded nearly two decades ago. Either way, 2024 is shaping up to be a make-or-break year for what was once the industry's most unassailable growth story.

The post Tesla Is Falling Far Behind the ‘Magnificent 7’ Group – Here’s Why That’s Good for the Market appeared first on Business2Community.

As AI technology gets smarter, especially as it moves towards Artificial General Intelligence (AGI), which is like human-level intelligence, there's a growing need to make sure it’s safe and doesn’t cause unexpected harm.

This is why this week, the organization shared a 27-page document called the "Preparedness Framework." The Preparedness Framework, described as a "living document", details OpenAI’s plan to keep an eye on, assess, and guard against serious risks that might come from their advanced AI models.

The Risks and the Response

The document covers a range of risks, including the misuse of AI for major cyberattacks and its possible role in developing dangerous weapons like biological, chemical, or nuclear arms.

The Framework outlines six key elements:

• Regular Risk Check-ups: OpenAI’s team keeps a close watch on the risks that come with advanced AI. They do ongoing research and evaluations to spot any new dangers that might pop up.
• Staying Ahead of Threats: The focus is on identifying risks that haven't yet been thought of, ensuring they're prepared for anything unexpected.
• Different Types of Risks: The risks are sorted into categories like cybersecurity, chemical and biological threats, and more. Each is monitored to see if the risk level increases, which would then trigger specific actions to reduce those risks.
• Strict Safety Rules and Extra Security: OpenAI has set safety standards for its AI models. Models have to meet these standards to be used or developed further. If a model is risky before they put safety checks in place, it gets extra security to make it safer.
• Teamwork for Safety Decisions: The safety plan involves various teams within OpenAI, bringing different skills and views to the table, especially in urgent situations.
• Continuous Updates and Independent Reviews: The plan is regularly updated with new information and findings. OpenAI also makes sure to get its work checked by outside experts to maintain transparency and accountability.

The Framework is flexible, meaning it can change and adapt as new information and research come in. It features a 'Scorecard' that OpenAI will regularly update, reflecting the latest findings in AI safety.

The Scorecard System

OpenAI's Preparedness Framework includes a 'scorecard' system to monitor the safety of its AI models, explained here in clear, straightforward terms:

• Risk Categories: The system evaluates AI models in several areas, including cybersecurity, chemical, biological, radiological, nuclear threats, persuasive power, and autonomy.
• Safety Levels: Each model is assessed and given a safety rating. There are four levels of safety risk, indicating how safe a model is after safety checks (post-mitigation) have been applied.
• Using the Models: Based on their scores, only models that are rated 'medium' risk or lower after safety checks can be used publicly. Models that get a 'high' risk rating or lower can still be worked on and improved.
• Tailored Security Measures: Models that show high or critical risk before safety measures (pre-mitigation) are subjected to extra security measures. This ensures that even the riskier models are made safer before they are further developed or used.

This scorecard system is a key part of OpenAI's effort to ensure that their AI models are safe and responsibly managed throughout their development and use.

Leadership Stability and Its Impact on AI Safety Initiatives

In the backdrop of unveiling its new AI safety plan, OpenAI has also navigated a significant leadership crisis. Sam Altman, the co-founder, was unexpectedly fired, leading to a massive response from the company's employees. Nearly all staff threatened to quit unless Altman was reinstated.

Fortunately, the crisis was resolved swiftly. Just twelve days after Altman's dismissal, he was reappointed as CEO. OpenAI also announced a revamped board of directors, with Microsoft joining as a non-voting observer. This move came after OpenAI’s stakeholders and board agreed to bring back Altman to stabilize the company.

Despite the turmoil, OpenAI has emerged unscathed, maintaining its staff and leadership. The company's focus now is to build trust, enhance transparency, and prevent future internal disputes.

The recent challenges within OpenAI and how they were resolved are really important to the company's focus on AI safety. Having steady and forward-thinking leaders is key to making sure rules about AI safety, like the "Preparedness Framework," are enforced. Leaders need to make decisive and responsible decisions, especially when it comes to advanced AI like AGI.

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IT Minister Ashwini Vaishnaw highlighted the global consensus on AI’s potential, benefits, and risks. He mentioned that the summit aims to align with international viewpoints and past agreements, and that the ultimate goal is to produce a consensus-driven declaration document by the end of GPAI 2023.

GPAI aims to connect theory and practice in AI, fostering international collaboration across various sectors. It includes 28 member countries and the European Union (EU), but China is not a member of the GPAI. The past summits were held in Montreal, Paris, and Tokyo.

[embed]https://twitter.com/_DigitalIndia/status/1734393129745121579[/embed]

India's Strategy at the GPAI Summit

Vaishnaw said that the GPAI declaration will have two aspects highlighting India’s stance around AI.

The first is to evaluate the use of AI in sustainable agriculture, adding to the previous GPAI themes including healthcare, climate action and building a resilient society. The second is on collaborative AI — in line with our DPI approach.

The Indian Express has previously explained India's plan to use a Digital Public Infrastructure (DPI) strategy for AI. This involves creating underlying systems, including databases and computing capacity, to help spread AI more widely. India has already used this approach with its Aadhaar biometric identity program and the Unified Payments Interface (UPI) payment system.

OpenAI's Involvement and Global AI Governance

Amid the evolving global landscape of AI regulation, the participation of key AI industry figures like Anna Makanju, Vice President of Global Affairs at OpenAI, at the GPAI Summit gains significance. During her address, she said:

We have learnt how important it is to develop governance models for AI. We have worked with the Biden Administration and G7… We must develop an international body to ensure that the most powerful technology is safe and the benefits of it are equally distributed.

Makanju's views are especially relevant considering the recent upheaval at OpenAI. The company, famous for ChatGPT, saw shifts in its leadership, including CEO Sam Altman's controversial exit and return, and Microsoft joining its board.

International Advances in AI Regulation

Globally, AI regulation is evolving. The EU recently agreed on a provisional AI Act, setting clear rules for AI use, especially in law enforcement, and allowing complaints against violations. It places strong limitations on facial recognition and AI that manipulates human behavior, with strict penalties for non-compliance.

Last month, Group 7 (G7) announced the Hiroshima AI Process, which focuses on creating guidelines for AI's safe development, emphasizing transparency, risk management, and global challenges like climate change and health. It encourages international cooperation and the continuous evolution of standards to harness AI's potential responsibly.

Furthermore, the United Nations (UN) also stepped up. The UN's AI initiative, led by a high-level advisory body, aims to use AI for global challenges and sustainable development goals. It focuses on starting global discussions on AI governance, understanding risks like misinformation, and promoting AI's application in critical areas like public health and education.

Previously, the U.S. issued an executive order for AI oversight and safety standards, marking a significant step by the Biden Administration in AI regulation. This order targets threats posed by AI and oversees the safety of AI technologies like ChatGPT and Google Bard.

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The company has already secured nearly $135 million from four investors, with the initial sale happening on November 29. This leaves $865.3 million yet to be sold. The filing indicates a "binding and enforceable agreement" for the acquisition of the remaining shares.

The company has also set a minimum investment threshold of $2 million for external investors.

This equity offering is a major step for x.AI as it looks to grow bigger. Selling shares not only brings in essential capital but also potentially diversifies the company's shareholder base.

The funds raised from this equity offering are pivotal for x.AI’s strategic expansion. With $135 million already secured, x.AI is demonstrating strong initial investor confidence. The funds from this offering are expected to fuel research and development, expand business operations, and possibly fund strategic acquisitions or partnerships. This is essential for x.AI to stay competitive in the fast-moving world of AI.

A key part of x.AI's expansion strategy is the development of its new chatbot, Grok. Launched in November 2022 for testing, Grok is positioned to challenge prominent AI chatbots like ChatGPT and Google's Bard. Its unique personality and ability to handle edgier questions differentiate it in the crowded AI market.

https://twitter.com/elonmusk/status/1731996930312405224

By incorporating Grok into X's Premium+ subscription, x.AI is not just enhancing its product offering but also aiming to increase user engagement and compete with AI giants such as OpenAI and DeepMind. This move by Musk and x.AI is a strategic attempt to catch up and make a mark in an industry led by these established players.

Elon Musk's Journey into AI and the Vision Behind x.AI

Elon Musk, famous for his leadership at Tesla and SpaceX, stepped into the world of AI by starting a new company called 'x.AI'. At x.AI, Musk is in charge as the director, with Jared Birchall as the corporate secretary.

Musk's plans for xAI are not limited to this new company alone. He aims to incorporate AI into his other ventures, including Tesla and SpaceX. For example, Tesla is focusing on using AI for various purposes, such as robotics, automation, and unique projects like the Tesla Bot and AI chips for self-driving cars.

This isn't Musk's first time venturing into AI. He was crucial in starting OpenAI, which created the well-known ChatGPT chatbot. Musk left OpenAI in 2018 before it split into a for-profit company because it conflicted with his other business activities, but he continues to be a significant voice in the AI field, often pointing out its fast growth and the dangers that come with it.

Musk's concerns about AI were highlighted earlier this year when he joined other experts in calling for a pause in the development of AI systems more advanced than GPT-4. This call stemmed from concerns over the lack of control and understanding of these powerful AI systems.

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We're entering a period of great uncertainty, where we're dealing with things we've never dealt with before. And normally, the first time you deal with something totally novel, you get it wrong. And we can't afford to get it wrong with these things.

Highlighting the seriousness of the issue, Hinton also mentioned that if we handle these advancements poorly, "they might take over... yes. That's a possibility."

[embed]https://www.youtube.com/watch?v=oyvs1iy1wrE[/embed]

A Call for Caution: The AI Community's Growing Concerns

His straightforward comments reflect a growing worry within the AI community about the fast pace of AI technologies without being properly prepared.

Supporting Hinton's worries, a recent statement from a nonprofit focused on creating safe AI, the Center for AI Safety, expressed the shared concerns of hundreds of AI leaders and researchers about the fast expansion of AI. Geoffrey Hinton was among the signers, along with leaders from major tech companies like OpenAI, Microsoft, and Google.

The statement also emphasized the need for proper preparation and a cautious approach to avoid potential missteps that could have irreversible consequences.

Machine Versus Man: The Potential of AI Surpassing Human Intelligence

The discussion between Pelley and Hinton on 60 Minutes revealed many startling insights about the future of AI.

Hinton, known for his groundbreaking work in AI, shared his worries about machines possibly becoming smarter than humans. This concern is real as AI is rapidly evolving, learning more and more every day.

The interview also touched upon Hinton's early days, which were filled with skepticism from the academic community during the initial stages. Despite this, he kept working on exploring the idea of neural networks, showing a strong will that eventually led to major discoveries in AI.

It took much, much longer than I expected. It took, like, 50 years before it worked well, but in the end it did work well… I always thought I was right [about neural networks].

Hinton’s thoughts on what AI can do now and in the future were both intriguing and a bit alarming. He believes that AI systems, with their ability to learn and think, might one day outsmart humans.

I think they may be [better at learning than the human mind], yes. And at present, they're quite a lot smaller. So even the biggest chatbots only have about a trillion connections in them. The human brain has about 100 trillion. And yet, in the trillion connections in a chatbot, it knows far more than you do in your hundred trillion connections, which suggests it's got a much better way of getting knowledge into those connections - a much better way of getting knowledge that isn't fully understood.

A Healing Touch: AI's Promise in Revolutionizing Healthcare

The potential benefits of AI in healthcare, as highlighted by Hinton, show a promising side of what AI can achieve. From interpreting medical images to designing drugs, AI's contribution to healthcare can be life-changing.

AI is already comparable with radiologists at understanding what's going on in medical images. It's gonna be very good at designing drugs. It already is designing drugs. So that's an area where it's almost entirely gonna do good.

In fact, there is already evidence that AI is revolutionizing medicine. By sifting through extensive data to identify potential compounds, AI cuts down the drug discovery timeframe drastically, as showcased by biotech startup Kantify. Additionally, collaborations between AI firms and major drugmakers, like the UK startup Causaly, are paving the way for more affordable and quicker drug development.

The Two Edges of AI: Uncovering the Risks Alongside the Rewards

However, the flip side of AI presents risks like unemployment, fake news, and the misuse of AI in military operations, which are equally concerning.

Well, the risks are having a whole class of people who are unemployed and not valued much because what they-- what they used to do is now done by machines.

Learning from History: Hinton's Reflection on AI, Governance, and Global Responsibility

Hinton stated that he has no regrets towards his work in AI due to its potential for good. But he says now is the time to study AI, for governments to set rules, and for a global agreement to stop the use of military robots. He spoke of Robert Oppenheimer, who, after making the atomic bomb, fought against the hydrogen bomb - a man who changed the world but found it out of his control.

It may be we look back and see this as a kind of turning point when humanity had to make the decision about whether to develop these things further and what to do to protect themselves if they did.

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The impact of artificial intelligence (AI) on various industries, including healthcare and finance, has been remarkable--and as AI technology continues to progress, its potential to improve the lives of underprivileged individuals worldwide is becoming increasingly evident as well.

In India, for example, AI is being used to help impoverished citizens overcome language barriers and gain access to government assistance programs. AI-powered chatbots are assisting low-income individuals in navigating complex bureaucratic processes to receive the help they need.

Bridging the Gap with Artificial Intelligence

Meanwhile, Bangalore is conducting trials of AI to enable some of the country's poorest individuals to access government anti-poverty initiatives while avoiding bureaucratic hurdles and corruption.

https://twitter.com/japantimes/status/1669187675276886016

Vijayalakshmi, a cook from Jayanagar who makes ends meet on a mere $100 per month, found herself unexpectedly involved in this AI initiative. Typically, her smartphone usage doesn't extend beyond basic tasks and English isn't in her linguistic arsenal.

Yet, one hot April afternoon, she found herself experimenting with artificial intelligence alongside her fellow domestic workers. In her native tongue of Kannada, she asked a bot about educational scholarships.

To her surprise, a lifelike voice answered promptly, detailing the governmental assistance available to her teenage son. This interaction serves as an illustration of the profound societal impact artificial intelligence can have.

Artificial Intelligence: An Equalizer for Social Inequality

While concerns about AI's role in disinformation and job displacement remain, the trials in Bangalore and Mewat in northern India demonstrate its potential as a tool for promoting social equality. Artificial intelligence can help with professional communications, empower those without language skills, and assist people with disabilities, such as the visually impaired who use BeMyEyes as a personal assistant.

India, where approximately 16% of the population lives in poverty, stands to benefit greatly from AI's ability to remove language and tech barriers. Unlike China, which has prohibited the use of ChatGPT, or the US and UK, which are considering AI regulation, India has fully embraced AI.

Indian ministers contend that the country can leverage AI to address language, education, and cultural inequalities without resorting to restrictive regulations. In India, several AI chatbots are being developed to help the underprivileged access legal justice, provide farming advice, and support migrant workers in urban environments.

https://twitter.com/satyanadella/status/1661131002515955714

Microsoft CEO Satya Nadella, who is originally from India, has also expressed optimism about AI's potential to improve the lives of remote villagers in the country. Nadella sees AI as a tool that can quickly diffuse knowledge and technology across the globe, leading to a more equitable distribution of resources.

Despite the potential benefits of AI, its rapid proliferation has raised concerns about political manipulation, health misinformation, and hyper-targeted advertising.

https://twitter.com/EconomicTimes/status/1667282923932753921

Some experts, including OpenAI CEO Sam Altman, have called for AI regulation, while others have warned of its potential existential risks. The importance of consent, data privacy, and security is amplified in India when working with individuals who lack technical skills and formal education.

Overcoming Bureaucracy and Corruption with AI

Back in Bangalore, many of the women testing ChatGPT had previously given up on receiving aid due to language difficulties and rampant corruption. Now, with the introduction of Jugalbandi, a bot providing multi-language translation services, they see a new path.

https://twitter.com/livemint/status/1669233283803099136

With the assistance of machine translation software containing millions of parallel sentences in various Indian languages and thousands of hours of spoken dialogue for recognition, Jugalbandi can now comprehend and respond to questions in rural dialects in the same language.

Artificial Intelligence, however, is not a magic wand. The social challenges in India are complex and enormous, and as Saurabh Karn, who led the Bangalore trials, admits, they are too big for AI to solve alone. But for women accustomed to bureaucratic hurdles and corruption, the advent of AI provides a glimmer of hope.

Yashoda, a domestic worker who participated in the trials, succinctly sums up the potential impact: “The robot can’t throw our application in the waste bin like the government official does when he’s dissatisfied with the bribe amount.”

But while AI is making strides in bridging the linguistic and literacy gap, it simultaneously underscores another division: the digital divide.

A group of waste pickers in a neighborhood at the far end of Bangalore, who spend their days collecting and selling recyclable waste, mostly don't own smartphones, thus revealing how AI can inadvertently deepen the gap between the technologically privileged and the deprived.

Meanwhile, AI has also inadvertently awakened a survival instinct in Vijayalakshmi, the domestic worker from Jayanagar, who is all too aware of the double-edged sword that is artificial intelligence.

"Bribe-rejecting robots are OK but don’t build any that can do house chores," she said. "I don’t want to lose my job to a robot."

As we tread deeper into the age of AI, Vijayalakshmi's words serve as a timely reminder that while artificial intelligence holds immense potential to better lives, the human element should always remain in the foreground.

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The cryptocurrency market is always active, never resting, and often difficult to comprehend. In the midst of all the noise and disorder, how can traders hope to stay on top of things?

Fortunately, by adopting a proactive trading strategy that emphasizes predicting market movements with all of the latest tools at their disposal, traders can dramatically increase their chances of success.

By harnessing the power of artificial intelligence and machine learning, traders can do just that. One platform on the cutting edge of the AI trading scene is yPredict.ai, which will be capable of extracting valuable insights from the massive amounts of data that flood the crypto market.

Explore yPredict: A premier tool for the next generation of crypto investors, offering cutting-edge technologies and doxed professional teams.

Why Invest in yPredict? Here are some compelling reasons from @CilinixCrypto on YouTube:

1️⃣ Amazing Platform: Experience the… pic.twitter.com/6CxKBi7t44

— yPredict.ai (@yPredict_ai) June 9, 2023

For an industry defined by unpredictability, yPredict offers the chance to outmaneuver a market that never sits still.

By quantifying the unquantifiable, this next-generation platform could mark a turning point in how traders tackle cryptocurrency's formidable complexities.

Visit yPredict Now

Leveraging Artificial Intelligence: The Capabilities of the yPredict Ecosystem

[caption id="attachment_2704694" align="alignnone" width="760"] yPredict Democratizes Trading With Artificial Intelligence[/caption]

YPRED token holders can access the yPredict analytics platform for free to analyze coins using data-driven insights and metrics.

They also have the option to pay for predictive model subscriptions through the yPredict Marketplace, receive incentives for participating in marketplace voting, and earn attractive APYs by staking $YPRED tokens.

Market Predictions: Artificial Intelligence-Backed Insights for Informed Trading

The yPredict.ai market predictions platform is an open platform to check cryptocurrency price predictions.

These predictions are generated through their in-house developed predictive models and selected marketplace developers' models.

Unlike many other financial information websites and blogs, yPredict will be transparent about the sources of predicted values and the methods of prediction.

yPredict Analytics: Building an Edge with Data

The yPredict analytics platform will use artificial intelligence to identify patterns in market behavior.

By analyzing transactional/tick data for each cryptocurrency, it will provide data-driven insights that help traders develop a statistical edge.

The platform will include features like pattern recognition, sentiment analysis, indicator analysis, and transaction analysis.

yPredict Marketplace: Connecting Developers and Traders

The yPredict marketplace platform is a forward-thinking platform connecting AI/ML developers and traders.

Developers can list their model's prediction results as a subscription service, thus generating passive income by creating AI/ML models.

Traders, meanwhile, can choose from hundreds of predictive models and subscribe to the ones they prefer.

yPredict Terminal: Advanced Trading for Pros

Understanding that trade execution is as crucial as research, the yPredict team has conceptualized the yPredict Terminal.

This sophisticated trading platform will cater to pro traders, emphasizing speed, a variety of order types, and order expiration.

The Terminal is designed to be compatible with yPredict Analytics and Marketplace modules and will allow instant order placement on a trading signal alert.

YPRED Tokens: Building a Stronger, More Efficient Predictive Modeling and Trading Ecosystem

A key component of the yPredict ecosystem is the YPRED token, a Polygon Matic chain-based token designed with powerful utilities and staking opportunities.

As each new platform subscription adds to the staking pool, it consistently maintains an attractive Annual Percentage Yield (APY).

The YPRED token's design empowers and supports the growth and economy of yPredict. It serves two main participants: developers and traders.

Developers are incentivized to offer their predictive models on the platform, thereby creating a passive income opportunity.

Traders, on the other hand, can use YPRED tokens to purchase subscriptions to these predictive models.

Just by owning YPRED tokens, traders gain free access to the yPredict Analytics platform and high APY staking reward pools.

YPRED tokens are being developed and will be deployed on the Polygon chain, offering several benefits such as Ethereum compatibility, scalability, security, and a developer-friendly environment.

yPredict’s Artificial Intelligence-Backed Platform: Building a Better Crypto Trading Ecosystem

For traders struggling amidst the crypto market’s chaos, YPredict.ai could prove to be a secret weapon.

By analyzing huge volumes of data, this platform will identify the connections that can be difficult for humans to perceive.

With robust analytics, predictive modeling, and a marketplace connecting developers and traders, yPredict will offer an ecosystem to help traders navigate an industry where change is the only constant.

Visit yPredict Now

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Billionaire investor Paul Tudor Jones who invested in bitcoins in 2020 has said that he would always keep a portion of his portfolio in digital assets. He also talked up AI and said it would create the next “productivity boom.”

Jones’ views on bitcoin and AI are in sharp contrast to fellow billionaire Warren Buffett who compared AI to an “atom bomb” earlier this month. The “Oracle of Omaha” has an even harsher view of bitcoins and termed it “rat poison squared” in 2018.

Meanwhile, Jones sees cryptocurrencies as a hedge against inflation and compared investing in them to buying gold in the 1970s.

At that time, gold prices rose quickly due to the oil crisis and high inflation rates. Mentioning Bitcoin's capped supply of 21 million, Jones stated, “I’ve always believed in having a small investment in it because it’s the only asset humans can’t change the supply of.”

Notably, global central banks – especially in developed markets – went into a money printing overdrive in 2020 amid the COVID-19 pandemic.

The current inflationary environment is partially due to the monetary policy excesses between 2020 and 2021.

Jones said, “So I’m sticking with it (Bitcoin), and I’m going to always stick with it as a small diversification in my portfolio.”

• Read our guide on buying Bitcoin with PayPal

While a section of the market is apprehensive about cryptocurrencies – many like Jones and fellow billionaire Stanley Druckenmiller advocate allocating a portion of portfolio to them.

Paul Tudor Jones is Invested in Bitcoins

Notably, after the crash last year, Bitcoin has rebounded and is among the best-performing assets of 2023.

Along with talking up cryptocurrencies, Jones also spoke about AI in the CNBC interview.

Jones stated, “I believe we will see a more divided market than ever in the next five to ten years, because I think the rise of large language models and artificial intelligence will lead to a productivity surge that we’ve only experienced a few times in the past 75 years.”

Multiple companies are turning to AI to enhance their productivity and Amazon has said that it would use AI to optimize its delivery mechanism.

Paul Tudor Jones on AI

Tech companies including Alphabet, Microsoft, IBM, Slack, and Meta Platforms are integrating AI into their products to make them even more attractive to users.

IBM intends to replace around 7,800 roles with AI which would help it lower costs structurally.

• Read our guide on the best AI stocks

Meanwhile, along with Buffett, his deputy Charlie Munger is also apprehensive about the AI “hype.”

Munger however sees AI making a mark in manufacturing and pointed to the increasing automation at China’s electric vehicle giant BYD – a Berkshire Hathaway portfolio company.

All said, like every major technology, AI might lead to disruption – including the elimination of several jobs. However, many, including OpenAI CEO Sam Altman believe that AI would also help create many better jobs.

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Amazon would use AI to speed up customer deliveries and decrease the distance that products need to travel before they finally reach customers.

Companies across the globe are embracing AI and Amazon – which is the world’s largest e-commerce platform – is also turning to AI.

Speaking with CNBC, Stefano Perego, Amazon’s vice president of customer fulfillment and global ops services for North America and Europe discussed how the company is incorporating AI to optimize its deliveries and logistics.

Perego said that Amazon would use AI to optimize the transportation of products and among others, it would help in predicting the weather along the route.

The company would also use AI to help customers find the desired products.

Perego said that Amazon would especially use AI for inventory management.

He said, “I’m sure you know about the wide range of options we provide to our customers. Think about how complicated it is to decide where to put that unit of inventory. We need to place it in a way that shortens the distance to fulfill customer orders and speeds up delivery.”

• Read our guide on the best AI stocks

Notably, amid its cost-cut push, Amazon has been optimizing its delivery mechanism and is moving to a more regional model.

It has divided the US markets into eight different regions and now 76% of the orders get fulfilled within the region – as compared to 62% a year back.

Amazon Turns to AI For Optimizing Deliveries

Perego also said that Amazon is now increasingly using robotics for completing repetitive tasks at fulfillment networks. Perego termed robotics as “collaborative robotic” and said they would “transform” and not “substitute” the jobs.

Notably, Amazon has announced 27,000 corporate layoffs this year. In absolute terms, its layoffs are the highest among FAANG peers.

The company has also cut the strength of warehouse employees after admitting to being overstaffed.

Almost all the tech companies are on a cost-cut overdrive and in March Amazon paused the construction of its HQ2 in Virginia – the site that it selected for its next headquarters after a nationwide competition in 2017.

However, things have changed since then and the revenue growth of tech companies has come down almost across the board.

Take for instance, in 2022, Amazon’s revenues rose by only 9% which is the lowest on record. Also, AWS revenue growth slumped to 20% in Q4 2022 which is the slowest since Amazon started to report the segment’s earnings separately.

Companies Turn to AI to Revive Their Fortunes

Along with cost cuts, AI has been another common thread among tech companies. While companies are cutting costs elsewhere – their purse strings are wide open when it comes to AI.

• Read our guide on the best AI crypto projects

Microsoft, among the investors of ChatGPT’s parent company OpenAI, has invested an undisclosed amount of money in Builder.ai – an AI startup that helps those without coding languages build applications.

Companies like Amazon see AI as a massive revenue opportunity as well as a tool to structurally lower their cost base.

Meanwhile, regulators are also scrambling to understand the risks and opportunities associated with AI.

Tomorrow, OpenAI CEO Sam Altman would testify before the Senate Judiciary subcommittee on privacy, technology, and the law on Tuesday in a hearing that’s titled – “Oversight of AI: Rules for Artificial Intelligence.”

The testimony was preceded by a meeting between US Vice President Kamala Harris and CEOs of OpenAI, Anthropic, Microsoft, and Alphabet.

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When we think of Goldman Sachs, AI wouldn’t be the first thing that might come to our mind. However, the Wall Street biggie created Louisa an AI-powered social media platform for corporate use.

Louisa emerged from Goldman’s incubator program which was floated by the company’s CEO David Solomon and encouraged employees to pitch startup ideas which can then be developed internally.

Goldman Sachs has now spun off Louisa and made it an independent company. Rohan Doctor, who’s the founder and CEO of Louisa is upbeat on the company’s prospects as an independent entity.

In an interview, he said, “Think of Louisa as an A.I.-powered LinkedIn on steroids.”

Doctor added, “We have smart profiles and a smart network, and Louisa reads millions of articles a week from 250 providers and begins connecting people” based on possible deals gleaned from news.”

Doctor said that while companies like Goldman Sachs can benefit immensely through shared knowledge and contacts of their employees – its not possible for employees to know every other employee in the company.

According to Doctor, “This is costing companies billions of dollars in terms of missed opportunities, disconnected colleagues and fractured client experiences.”

While Goldman Sachs said that Louisa has 20,000 monthly active users – it did not divulge much about the company’s finances including on how much money it spent to build the platform.

Goldman Sachs Spins Off Its AI-Powered Social Media Platform

AI has been making waves across multiple industries. Since Louisa is now an independent company, Doctor is pursuing new clients and it has already signed up a commercial bank and a venture capital fund for the platform.

An increasing number of tech companies have announced AI forays and at its annual Think conference earlier this week, IBM unveiled a new AI and data platform called Watsonx for enterprise customers.

The company sees AI and cloud as its key growth drivers and has been taking steps to grow these businesses.

• Read our guide on the best AI stocks

Meanwhile, Doctor believes that generative AI and hybrid/remote work are two key enablers for Louisa.

Doctor Sees a Massive Opportunity for Louisa

While admitting that OpenAI has done a “phenomenal” job, Doctor added, “We can use it to sort of map out what’s in people’s minds and how they want to describe themselves in seconds.”

Notably, AI is perhaps the hottest investment theme currently even as companies have scaled back their bets elsewhere.

Microsoft, among the investors of ChatGPT’s parent company OpenAI, has invested an undisclosed amount of money in Builder.ai – an AI startup that helps those without coding languages build applications.

Meanwhile, regulators are also scrambling to understand the risks and opportunities associated with AI.

Altman would testify before the Senate Judiciary subcommittee on privacy, technology, and the law on Tuesday in a hearing that’s titled – “Oversight of AI: Rules for Artificial Intelligence.”

The testimony was preceded by a meeting between US Vice President Kamala Harris and CEOs of OpenAI, Anthropic, Microsoft, and Alphabet.

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European Union lawmakers have voted to incorporate tougher amendments to the region’s widely anticipated AI Act which could be the first comprehensive AI regulation globally.

The EU’s upcoming AI Act would cover several aspects like biometric surveillance, recognitions, and other applications like generative AI.

The European Commission has been working on the AI Act for around two years but a sense of urgency now seems to be creeping in – amid the growing popularity – and the multiple concerns associated with generative AI.

Members of the European Parliament (MEPs) agreed to a ban on emotion recognition, biometric surveillance, and predictive policing AI systems.

https://twitter.com/Europarl_EN/status/1656580706913452033

The draft proposes to classify AI tools based on the perceived risk levels ranging from minimal to unacceptable.

Greens MEP Kim van Sparrentak told Reuters, “This vote is a milestone in regulating AI, and a clear signal from the Parliament that fundamental rights should be a cornerstone of that.”

Sparrentak added, "AI should serve people, society, and the environment, not the other way around."

The proposed Act would now be put before a plenary vote of the European Parliament in June. It would then be followed by a “trilogue” between representatives of the European Parliament, the Council of the European Union, and the European Commission.

EU Moves Ahead on the AI Act

According to the EU, “The aim of a trilogue is to reach a provisional agreement on a legislative proposal that is acceptable to both the Parliament and the Council, the co-legislators.”

Once the law is enacted, it provides a two-year grace period for compliance.

While multiple countries including the US are contemplating AI regulations, Europe is at the forefront of framing regulations for the industry.

Meanwhile, after lagging behind Europe, the US is also getting its act together. Earlier this month, US Vice President Kamala Harris met CEOs of Anthropic, Microsoft, Alphabet, and OpenAI.

• Read our guide on the best AI stocks

Next week, OpenAI CEO Sam Altman would testify before the Senate Judiciary subcommittee on privacy, technology, and the law on Tuesday in a hearing that’s titled – “Oversight of AI: Rules for Artificial Intelligence.”

Countries Are Looking to Regulate Artificial Intelligence

Earlier this month, UK’s CMA (Competition and Markets Authority) also launched an initial review of AI models .

CMA said that its initial review would examine three aspects which are

• Examining how markets and use for foundation models could evolve
• Exploring the opportunities and risks with respect to competition and consumer protection
• Coming up with guidelines to protect consumers and competition

Other Western countries are also contemplating how to regulate AI. Last month, the digital ministers of G7 issued a joint statement after the conclusion of their 2-day meeting in Japan and said that the development of artificial intelligence should be based on democratic values.

While authoritarian regimes have censored AI, the Western World is looking to embrace it – with enabling regulations that would help realize the technology’s potential while reducing the associated risks.

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Qualcomm Inc's artificial intelligence chips outperformed those made by Nvidia in power efficiency during the MLPerf test results released on Wednesday. As per the results from MLCommons, Qualcomm’s chips surpassed Nvidia’s in two of the three power efficiency tests, while a Taiwanese startup outperformed both companies in the third test.

When it comes to training AI models with large amounts of data, Nvidia leads the market. However, after these models are trained, they are used more widely for inference, performing tasks like determining if an image has a cat and generating text answers to questions.

As companies across the globe continue to adopt AI technology into their products, the market for data center inference chips is expected to expand significantly. However, with the integration of AI into products comes extra costs such as computing power. As such, companies such as Google are already looking into ways to limit the additional expenses that this would entail.

Electricity is one of those significant costs, and Qualcomm has utilized its experience creating CPUs for battery-powered devices like smartphones to produce a chip called the Cloud AI 100 that strives for economical power consumption.

MLCommons is an engineering consortium that maintains testing benchmarks widely used in the AI chip industry. The task of operating neural networks in production is known as AI inference processing, and every six months, MLCommons releases a new set of benchmarks for this activity

Qualcomm Tops The Power Efficiency Tests

In the results for the most recent activity, Qualcomm's AI 100 chip outperformed Nvidia's flagship H100 chip at efficient use of power when classifying images. Qualcomm's processors achieved 197.6 server queries per watt whereas Nvidia attained 108.4 queries per watt. However, with 227 queries per watt, Neuchips, a startup founded by renowned Taiwanese chip academic Youn-Long Lin, won the benchmark.

In the object detection test, Qualcomm outperformed Nvidia with a score of 3.2 queries per watt as opposed to Nvidia's 2.4 queries per watt.

Nvidia, however, won a test of natural language processing, in both absolute performance terms and power efficiency terms. Natural language processing is mainly used in chatbot systems such as ChatGPT, Nvidia achieved a sampling rate of 10.8 samples per watt, followed by Neuchips at 8.9 samples per watt and Qualcomm at 7.5 samples per watt.

The other submitters included Alibaba, ASUSTeK, Azure, cTuning, Deci, Dell, Gigabyte, H3C, HPE, Inspur, Intel, Krai, Lenovo, Moffett, Nettrix, Neural Magic, Quanta Cloud Technology, Rebellions, SiMa, Supermicro, VMware, and xFusion.

The companies made submissions for various other tasks including medical imaging, speech-to-text, language processing, and recommendation in addition to image classification and object detection.

Nvidia On A Winning Streak In Performance

While Nvidia was greatly challenged in terms of power efficacy, the NVIDIA H100 Tensor Core GPUs delivered the highest performance in every test of AI inference. In addition, the GPUs delivered up to 54% performance gains from their debut in September, thanks to software optimizations.

https://twitter.com/NVIDIADC/status/1643693977571569664?s=20

Furthermore, the company debuted the new NVIDIA L4 Tensor Core GPUs whose performance rate was more than three times that of T4 GPUs from earlier generations.

Notably, the number of software engineers employed by NVIDIA is significantly more than that of many of its rivals, and these engineers keep improving the performance of new chip generations.

This gives Nvidia a competitive advantage and any company trying to beat them will have a very tough time doing so, especially in the data center and edge applications that require the flexibility of running many models.

While Qualcomm did not top any of the performance tests, the company demonstrated a 75% performance improvement since they began this journey 3 years ago.

Related News:

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Everyone is talking about ChatGPT and we have compiled the top 100 statistics everyone needs to know about the internet sensation. That's not surprising as ChatGPT is the fastest-growing app in history.

ChatGPT is the new artificial intelligence chatbot from OpenAI that has captured the public imagination.

The chatbot is being hailed as the most exciting thing that has happened in technology since the advent of the internet and the first search engine or the launch of the iPhone.

For sure, there's been a lot of hype, but it may well be justified. ChatGPT can answer queries in 95 languages in a human-like conversational style, learning from your responses as it goes.

Ask any question and it will be able to provide a text response, although as we see in our 100 top ChatGPT statistics below, there are limitations.

Ask ChatGPT to write a 400-word assignment on The Enlightenment and it will do that:

Fancy a trip to the stores to buy some clothes? It will provide you with the relevant list of retail outlets.

Struggling with javascript for a web page you are coding – ask the right query and ChatGPT will generate the code for you.

Because ChatGPT is so human-like in its comprehensive and mostly accurate answers, it threatens to do away with search engines, or at least to force a radical reimagining of them.

Google and a host of other tech companies are racing to catch up with OpenAI, but for now it is ChatGPT that is the fastest-growing app ever.

If you haven’t used ChatGPT yet, set up an account and get started here: https://chat.openai.com/chat

And if you want to find out everything there is to know about ChatGPT in 1,800 words, read on.

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What is ChatGPT?

1. ChatGPT is an artificial intelligence (AI) chatbot – a conversational AI system.

2. GPT stands for Generative Pre-trained Transformer. GPT is a Language Model.

3. ChatGPT is a form of Generative AI – Generative AI refers to computer generation of text or images as a response to human input.

4. ChatGPT makes use of the Transformer model – a neural network that learns contextual information. Transformer was originally developed by Google Labs in 2017.

5. GPT and other language models are “trained” using Machine Learning (ML).

6. Language models like GPT use statistical and probabilistic techniques to predict the next word in a sentence based on the previous sentence or words.

A language model establishes the chances – probability distribution – of the next word being “valid”, valid in the sense that it resembles a sentence a human being would write.

7. The GPT language model generates relevant text in response to “system prompts” in the form of human-written questions.

8. Machine-learning refers to a computational tool for efficiently incorporating vast amounts of data that is reusable “out of sample”. In other words the data being consumed is not the data that was used to train the model in the first instance, hence “out of sample”.

9. This form of language modeling is known as an Autoregressive Language Model for deep learning.

10. Language models “learn” (through the training process) by consuming vast amounts of data.

11. Natural Language Processing (NLP), Natural Language Generation (NLG) and machine learning are all used to create and refine language models such as GPT.

12. ChatGPT uses Reinforcement Learning From Human Feedback (RLHF) to train the GPT language model. An initial model was trained using Supervised Fine-Tuning (SFT), where AI Trainers interact with the model directly as both user and AI assistant.

AI trainers ranked the conversations and this was further refined in an iterative process known as Proximal Policy Optimization (PPO), as shown in the infographic below:

13. ChatGPT and the GPT 3.5 language model it is based on were trained on an Azure AI supercomputing infrastructure. Azure is owned by Microsoft.

14. Azure provides the operating infrastructure for ChatGPT.

Essential statistics about OpenAI

15. OpenAI was founded in San Francisco, California, as a non-profit organization in 2015 with the mission, as embodied in the OpenAI Charter, to create “safe and beneficial” AGI.

16. ChatGPT is developed by OpenAI.

17. OpenAI was founded by Carlos Virella, Elon Musk, Greg Brockman, Ilya Sutskever, James Greene, Sam Altman and Wojciech Zaremba.

18. OpenAI’s mission is to make computers think like humans – Artificial General Intelligence (AGI).

19. Here is an excerpt from the opening paragraph of the OpenAI charter:

OpenAI’s mission is to ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity.

We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome.

20. Early board members included tech entrepreneurs Peter Thiel and Elon Musk. Elon Musk left the board in 2018 but remained a donor.

21. Elon Musk has distanced himself from OpenAI after criticizing Microsoft’s involvement.

22. In 2019 OpenAI became a profit-making enterprise (Open AI LP), controlled by the board of the original non-profit organization (OpenAI Inc).

23 GPT technology was first revealed to the public on 14 February 2019 as open source and known as GPT2, but requiring a proprietary license.

24. Other notable OpenAI technology includes DALL.E 2 – generates images from a text description.

25. ChatGPT is developing Point-E – software to develop 3D models from simple word prompts.

ChatGPT statistics

26. ChatGPT was launched on 30 November 2022 and is the fastest-growing app ever.

27. ChatGPT launched using the GPT 3.5 language model.

28. In December 2023 ChatGPT had 57 million users according to estimates by UBS analyst Lloyd Walmsley in a research note published on 1 February 2023, as reported by Barron’s.

29. In January 2023 ChatGPT was estimated to have 100 million users.

30. ChatGPT has reached 100m users in two months. By comparison it took TikTok nine months to reach 100 million users and Instagram 2.5 years.

31. In January 2023 ChatGPT had 672 million web visits, according to Similarweb.

32. ChatGPT averaged more than 13 million daily visitors in January 2023.

Investors in ChatGPT developed and owner OpenAI

33. In 2015 OpenAI raised $1 billion from investors.

34. Venture capital investors: Y Combinator; Reid Hoffman Association; Khosla Ventures; Matthew Brown Companies; Microsoft; Tiger Global Management; Andreessen Horowitz; Sequoia Capital; Bedrock Capital; Infosys; Jesica Livingston; Peter Thiel; Amazon Web Services (last three not included in table - source dealroom.co).

OpenAI early investors

35. Microsoft invested $1 billion in OpenAI in July 2019. It also joined a funding round in 2021.

36. On 23 January 2023 Microsoft announced it was investing a further $10 billion in OpenAI.

37. OpenAI CEO is Sam Altman (former president of Y Combinator, a seed round investor in OpenAI).

38. OpenAI President Greg Brockman.

39. OpenAI CTO Mira Murati.

40. OpenAI latest valuation: $29 billion.

Some of the things ChatGPT can do

41. Answer queries with a textual response in 95 languages.

42. Remember what users said earlier in the conversation.

43. Allows users to provide follow-up corrections.

44. Trained to decline inappropriate requests.

45. Write school assignments and essays.

46. Write code.

47. Pass an MBA.

48. Write a funny story.

49. Write a limerick.

50. Write a resignation letter to your employer.

51. Generate shopping lists for meals.

52. Create a list of the nearest Korean restaurants to you.

53. Bing helps ChatGPT do more. Bing uses Prometheus to deliver answers on events after 2021.

54. Microsoft’s Edge browser in consort with ChatGPT can, for example, instantly summarize the financial results of any two companies, compare them and generate key takeaways.

ChatGPT has limitations

55. Not very good at logical reasoning.

Here’s an example of a ChatCGT fail:

https://twitter.com/neuro_tarun/status/1598357991031705600

56. May occasionally generate incorrect information – could be a growing source of misinformation.

57. Sometimes ChatGPT is inaccessible because of load on servers, so. you may see a “busy” message, or more recently a message like this: “We're experiencing exceptionally high demand. Please hang tight as we work on scaling our systems.”

58. May occasionally produce harmful instructions or biased content.

59. Limited knowledge of world and events after 2021.

60. Not very good at math puzzles and brain teasers.

61. ChatGPT is not infallible so will get some things wrong.

62. Could infringe copyright.

63. Can lead to ‘hallucination’ – gives convincing yet wholly fictitious answers.

64. Cannot be relied upon for serious work (yet).

65. ChatGPT-powered Microsoft Bing search engine and Microsoft Edge web browser are for now only available on desktop.

More ChatGPT stats

66. Only answers questions on world affairs and events prior to 2021.

67. How much does answering a ChatGPT query cost on average? $0.36.

68. Each word generated by ChatGPT costs $0.0003.

69. Paid version of ChatGPT Pro costs $20/month.

70. ChatGPT is available in 161 countries, regions and territories.

71. ChatGPT is not available in China, Iran, North Korea, Russia, Venezuela and Belarus.

These could be the ChatGPT losers

72. All types of language and knowledge-based workers.

73. Publishers that rely on traffic from google links because if Bing/Edge powered by ChatGPT provides fuller answers in plain English text there’s no need to visit a site to receive less contextualized answers.

74. All manner of professionals and specialists.

75. Writers.

76. Educationalists.

77. Advertisers that rely on search engine results pages composed of links might find their ad links more difficult to place and still be as clickable.

78. Basic computer programmers.

79. Google.

"After I turn in this column, I’m going to do something I thought I’d never do: I’m switching my desktop computer’s default search engine to Bing."
Kevin Roose, New York Times

ChatGPT’s AI chatbot competitors

80. Google AI chatbot Bard. Introduced to the public at a demonstration on 6 February.

Among other things, Bard was asked: “What new discoveries from the James Webb Space Telescope can I tell my 9 year old about?”

One of Bard’s three bullet-pointed answers was incorrect when it claimed, incorrectly, that the James Webb Space Telescope “took the very first pictures of a planet outside of our own solar system.”

Google uses the LaMDA language model.

81. LaMDA differs from GPT by being trained on dialogue as opposed to web text. LaMDA stands for Language Model of Dialogue Applications. Like GPT, LaMDA is a Large Language Model (LLM).

These are the main LLMs:

82. Turing NLG (Microsoft).

83. Gopher, Chichilla (Deepmind).

84. Switch transformer, GLAM, PALM, LaMDA, T5, MT5 (Google).

85. OPT, Fairseq Dense (Meta).

86. GPT-3 versions such as GPT-Neo, GPT-J, & GPT-NeoX (Open-AI).

87. Ernie 3.0 (Baidu).

88. Jurassic (AI21Labs).

89. Exaone (LG).

90. China’s Baidu could be the major ChatGPT.

91. Baidu is launching its AI chat service in March.

In 2019 Baidu’s AI Chat scored 90.1 on the General Language Understanding Evaluation benchmark ERNIE model score. Its score beat Microsoft’s MT-DNN-SMART and Google’s TS models.

92. According to reports, Baidu’s ChatGPT AI chatbot will be called Ernie Bot.

93. Kunlun Tech says it will have its own version of a ChatGPT-like AI chatbot.

94. Other China-based competitors include: Alibaba, Tencent, NetEase, Kuaishou Technology, Inspur Electronic Information Industry, 360 Security Technology, Kunlun Tech and JD.com.

The ethics of generative AI and ChatGPT

95. New York City education department has banned ChatGPT.

96. A poorly trained AI chatbot can replicate societal biases

Microsoft’s Tay bot deployed on Twitter was withdrawn after generating sexist, racist and abusive language responses.

97. Lack of a system for disclosing when a response has been generated by an AI chatbot.

98. Generally, AI chatbot data usage, ownership and protection is not transparent.

99. Generally, there’s a need to guard against commercial bias built into the chatbot model to benefit certain companies.

100. Chatbot personas have traditionally been female, for example Amazon’s voice chatbot Alexa, but should they be gender neutral?

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The post Top 100 ChatGPT Statistics And Facts 2023 – Comprehensive AI Chatbot Guide appeared first on Business2Community.

Digg founder and prominent web3 investor Kevin Rose has just fallen fowl of a wallet hack. Rose apparently signed off on a number of malicious transactions in his Ethereum crypto wallet.

https://twitter.com/kevinrose/status/1618323487067869184

The hackers appear to have made off with dozens of expensive non-fungible tokens (NFTs), including 25 Squiggles NFTs and an Autoglyph NFT. The floor price, according to nftfloorprice.com, of Squiggles NFTs was last around 13 ETH, or just under $20,000. Autoglyph NFTs have low market liquidity, but were last traded for around 200 ETH (over $300,000).

Rose had been trying to sell his Autoglyph NFT for $539,000. In total, it looks like Rose has lost at least $800,000 in NFTs via the hack, which can be verified here on Etherscan. Rose urged his follower to avoid buying any Squiggles (and other NFTs) until they have been flagged.

Rose will be relieved that he did not lose his entire NFT collection, including the crown jewel of his collection – a grail zombie CyberPunk NFT that have in the past sold for millions of dollars.

https://twitter.com/JulianKlymochko/status/1618328315890405377

Third Major NFT Hack This Month

The attack on Kevin Rose is the third major incidence of NFT theft this month, according to web3 grift and criminal behavior news tracking website web3isgoinggreat.com.

Back on the 13^th of January, NFT GOD’s wallet was drained after his computer was infected with malware. NFT GOD lost all of his NFTs and crypto, including a Mutant Ape NFT which was then sold on for 16.65 ETH (around $25,800).

https://twitter.com/NFT_GOD/status/1614442000958324739

NFT GODS’ social media accounts were also hacked and used to send out phishing links to his base of followers. Meanwhile, on the 4^th of January, crypto influencer @CryptoNovo was hacked, losing NFTs were quickly flipped for a total of 417 ETH, worth around $525,000 at the time. CryptoNovo had paid at least double for the NFTs when they were first purchased back in 2021.

Crypto Safety a Key Concern For Investors

Fund safety has been identified as a key barrier to crypto adoption – if the risk of losing funds to robbers remain as high as it is, many will remain deterred from investing in/using crypto.

But crypto users can take steps to reduce their risk of losing funds. When crypto is stored on a platform like a centralized exchange, investors should set up 2 Factor Authentication whenever possible, which can be further strengthened by using Google’s Authenticator application.

Investors should also consider withdrawing funds to a hardware wallet, ensuring that they back up their seed phrase properly and using strong, varied passwords. When interacting with Decentralized Finance (DeFi) protocols, crypto users should take particular care to ensure they aren’t on a fake website or dApp that actually aims to steal their information/funds.

Related Articles

• Here’s How to Invest in the EV Charging Revolution With a New Blockchain Platform And Earn Carbon Credit Rewards
• Crypto Keeps Rising and the Dollar Keeps falling And Why That’s a Problem for the US Government

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The post Crypto Entrepreneur Kevin Rose Loses Around $800k Worth of NFTs in Hack appeared first on Business2Community.