James Wu’s Post

Safe Superintelligence Secures $1 Billion to Revolutionize AI with Safety, Strategy, and Scale In the competitive AI landscape, Safe Superintelligence (SSI), co-founded by Ilya Sutskever, is positioning itself as a key player with a mission to push AI beyond human capabilities, all while ensuring safety. With a $1 billion investment from top VC firms like Andreessen Horowitz, Sequoia Capital, DST Global, and SV Angel, SSI plans to scale its talent and computing power, focusing on R&D before hitting the market. This shift in focus highlights a growing trend in the AI sector: safety and long-term alignment over rapid deployment. While competitors like OpenAI, Anthropic, Google, and Meta race to lead in AI capabilities, SSI’s approach to scaling—rethinking how AI is built, not just expanding computing resources—could redefine the race. For companies competing in AI, the message is clear: spending on talent and R&D, alongside aligning with ethical frameworks, will shape the next wave of innovation. The industry is no longer about scaling for speed but scaling with strategy and vision. SSI’s thoughtful approach, alongside a trusted, cohesive team, could challenge the dominant players and reshape the AI landscape in a way that prioritizes both capability and safety. As the battle for AI supremacy intensifies, the question becomes not just who can build the fastest, but who can build the safest—and most transformative—systems. See article below for more details… #AI #SafeAI #Superintelligence #RethinkingAI #AIResearch #TechLeadership #FutureOfAI #ScalingAI #VentureCapital #AICompetition #OpenAI #SSI #Google #Meta #Anthropic #a16z #SequoiaCapital #DSTGlobal #SVAngel https://lnkd.in/gYNkUinj

💡 OpenAI Secures Billions in Funding: How Will It Give Back to Society? 🌍 With its recent funding round, OpenAI has raised billions, but the big question remains—how will it leverage these resources to benefit society? From advancing AI research to promoting ethical use and collaboration with diverse sectors, OpenAI has a unique opportunity to create a lasting impact. The focus now is on responsible innovation that empowers industries, communities, and individuals. Read full story here: https://lnkd.in/eEtKfyX5 OpenAI Open Innovation AI OPEN AI Open Ai Labs #AI #OpenAI #EthicalAI #TechForGood #Innovation #FutureOfAI #SocialImpact #Funding

I always read something interesting as we curate for my knowledge base, Teckedin, like this news from VentureBeat and this solution created by Anna Monaco "Paradigm’s software uses AI agents — built atop proprietary and open-source gen AI models from third parties including OpenAI’s GPT-4o and Meta’s Llama family, according to Fortune — to scour the web for the information the user desires and automatically populate the spreadsheet cells accordingly." #automation #spreadsheet #genai #AI #startup

After billions spent out there, "now", the "New Trend/Focus in AI" seems to be on the Shift from a World of Massive Pre-Training Clusters toward Inference Clouds, which are Distributed, Cloud-based Servers for Inference... discovering a 2nd Scaling Law, & this is the Scaling Law at a Time of Inference... In summary: A dozen AI Scientists, Researchers and Investors told Reuters they believe that these Techniques, which are behind OpenAI's recently released o1 Model, could reshape the AI Arms Race, and have implications for the types of resources that AI companies have an insatiable demand for, from Energy to Types of Chips. OpenAI declined to comment for this story. But now, some of the Most Prominent AI Scientists are speaking out on the Limitations of this “Bigger is Better” Philosophy. Ilya Sutskever, Co-Founder of AI Labs Safe Superintelligence (SSI) and OpenAI, told Reuters recently that Results from Scaling up Pre-Training - the Phase of Training an AI Model that use s a Vast Amount of Unlabeled Data to understand Language Patterns and Structures - have plateaued. “The 2010s were the Age of Scaling, now we're back in the Age of Wonder and Discovery once again. Everyone is looking for the next thing,” Sutskever said. “Scaling the Right Thing matters more now than ever.” Sutskever declined to share more Details on How his team is addressing the issue, other than saying SSI is working on an Alternative Approach to Scaling up Pre-Training. At the same time, Researchers at other top AI Labs, from Anthropic, xAI, and Google DeepMind, have also been working to develop their own versions of the Technique, according to five (5) people familiar with the efforts. “This shift will move us from a world of massive pre-training clusters toward inference clouds, which are distributed, cloud-based servers for inference,” Sonya Huang, a partner at Sequoia Capital, told Reuters. "We've now discovered a second scaling law, and this is the scaling law at a time of inference...

Key takeaways from yesterday's OpenAI DevDay in London and the Q&A with Sam Altman: The big takeaway? OpenAI is all about building integrated, powerful, and autonomous systems, focusing on long-term transformation rather than quick wins. 🚀 Here’s what the CEO of OpenAI shared about the future of AI: 1. **On Development & Investment:** - It’s not just about single models, but enhancing LLMs as a whole. - Trillion-dollar investments? Totally worth it for education and healthcare potential. 💰 - “Don’t build crutches for current limitations – create for future possibilities.” 2. **About AI Agents:** - Definition: "A system for long-term tasks with minimal oversight." - Killer features: parallel processing (300 calls at once) and extended autonomy. - Think of an AI Agent as that smart senior colleague you can trust with a week-long project. 3. **New O1 Features Announced:** - Function calling - Developer messages - Streaming - Structured outputs - Image understanding 🖼 💡 **Startup Tips:** - Focus on vertical solutions (like AI lawyers or engineers). - Build with future AI enhancements in mind. - Create things that amplify what LLMs can do, not just compensate. **On Hiring & Leadership:** - “I was over 30 when I founded OpenAI.” - Balancing young talent with experience matters! - The only requirement? Exceptional talent. 🔮 **5-Year Forecast:** - Tech will evolve at lightning speed. - Society will change slower than expected, but more profoundly. - Think transistors, not just the internet – a fundamental shift in computing physics. And a philosophical note from Sam Altman: “I don’t pray for God to be on my side; I pray to be on God’s side. Working on these models definitely feels like working alongside angels.” 🙏✨

François Chollet's exit from Google after nearly a decade isn't just another corporate shuffle—it's a pivotal moment for the AI industry. As the visionary behind Keras, Chollet has not only transformed deep learning but also challenged the status quo with his advocacy for neuro-symbolic AI. His departure opens the door to new ventures that could redefine how we approach AI. While many have relied on massive data and computational power, Chollet's focus on human-like reasoning and interpretability suggests a shift in paradigm. His upcoming company, although shrouded in mystery, has the potential to spark innovation in a field ripe for evolution. As we witness this transformation, let’s consider: Could the future of AI lie in collaboration rather than competition? Keep an eye on Chollet; his next moves could reshape our understanding of AI and its role in society. The future of intelligent systems might be more promising than we think!

It seems that AI is here to stay and that the bets investors are taking are huge. One might wonder if AI will deliver or if, at this point, is just another bubble such as the dot com bubble we faced before. Pros and Cons of AI Pros: Efficiency Gains: AI automates complex tasks, driving productivity. Innovation Catalyst: Sparks new industries and business models. Scalability: Enables rapid scaling with minimal human intervention. Cons: Regulatory Uncertainty: Ongoing concerns about ethical and legal implications. Market Volatility: Potential overvaluation and speculative investments. Job Displacement: Risk of significant unemployment in certain sectors. Analogy to the Dot-Com Bubble: Just like the dot-com era, AI is generating massive excitement and capital inflows. But are we on the brink of a new technological revolution, or is this another bubble waiting to burst? The difference lies in the foundational impact—AI, like the internet, could be transformative. However, discerning between lasting innovations and short-lived hype is crucial for investors. Is AI here to stay, or are we witnessing another speculative frenzy? Time will tell. I love the SSI term that I am sure we will begin to use more often. #AI #Investment #DotComBubble #Innovation #TechInvesting

Fascinating shift in AI landscape! Major AI companies are pivoting from the "bigger AI is better AI" philosophy. The traditional approach of throwing more data and computing power at AI models is reaching a limit - it isn't producing the breakthrough improvements we once saw. This comes straight from Ilya Sutskever, who pioneered these techniques at OpenAI before founding SSI (Safe Super Intelligence). Scaling up pre-training has plateaued. So what's next? Companies are now exploring "test-time compute" - essentially teaching AI to "think" more like humans by evaluating multiple possibilities before giving an answer. OpenAI's new "o1" model is already implementing this approach, and other major players (Anthropic, xAI, Google DeepMind) are following. This could reshape the AI arms race: - Less emphasis on raw computing power - More focus on innovative training techniques - Shift from massive training clusters to inference clouds This is actually great news for innovation. Instead of a brute-force race to build bigger models, we're entering what Sutskever calls "the age of wonder and discovery." It's no longer just who has a ‘bigger one’. It’s who has a smarter one. #ai #Innovation  https://lnkd.in/dVgwkmY7

#Plateau or just a break to get stronger? Are we reaching the limits of current AI, or is this just a pause before the next breakthrough? Ilya Sutskever co-founder of Safe Superintelligence and OpenAI recently suggested that scaling up pre-training — the phase where AI models learn language patterns from vast amounts of data — may have hit a #plateau. Data scientists are debating whether this “plateau” signals a limit or if it’s an #opportunity to explore new approaches. In my opinion, less than two years ago, tools like #ChatGPT were still emerging, #innovation rarely stops, it simply #evolves. Angeles Investors HITEC Salesforce Gartner Latino Leaders Magazine National Institute of Standards and Technology (NIST) Latino Corporate Directors Association (LCDA)

Interesting reporting here Reuters on the limitations of our current AI models. Turns out that to do better the machines also need thinking time! "“It turned out that having a bot think for just 20 seconds in a hand of poker got the same boosting performance as scaling up the model by 100,000x and training it for 100,000 times longer,” said Noam Brown, a researcher at OpenAI who worked on o1, at TED AI conference in San Francisco last month. OpenAI has embraced this technique in their newly released model known as "o1,” formerly known as Q* and Strawberry , which Reuters first reported in July. The O1 model can "think" through problems in a multi-step manner, similar to human reasoning. It also involves using data and feedback curated from PhDs and industry experts . The secret sauce of the o1 series is another set of training carried out on top of ‘base’ models like GPT-4, and the company says it plans to apply this technique with more and bigger base models." I see a lot of AI being used in carbon accounting and ESG modelling (as we are also exploring), but as we all know, not all data is equal. Benchmarking against competitors when using AI often means data from a PR article is viewed as an equivalence to an academic review. We need to train AI to think more critically. https://lnkd.in/evxhQCVu #ArtificialIntelligence #AIDevelopment #MachineLearning #ESGTechnology #DataQuality #FutureOfAI #StartupFunding #VentureCapital #PreSeedFunding #InvestInStartups #AngelInvestor Andrea Sommer Karina Godber