Satya Nadella

🗞️🗞️ Exciting news from IBM and Meta! 🤝 Llama 3 models are now available on #WatsonX. Collaborating with Meta, we're driving open and responsible AI forward. This is the way to go! #OpenInnovation

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On the latest Vital Signs, Nikhil Krishnan and I had a ton of fun chatting with Dr. Atul Butte. Dr. Butte is a professor at UCSF, Chief Data Scientist of the UC Health System, and a co-founder of numerous healthcare startups. In our conversation, Dr. Butte shared his takes on healthcare AI opportunities, challenges, hype, and more. A few highlights: ⚡LLM use cases, data, and growth LLMs are already helping to solve the “drudgery” aspects of medicine, such as automatically drafting SOAP notes and patient messages. Dr. Butte is excited about future applications of LLMs that can help with the “cognitive” aspects: with difficult medical problems an LLM might be able to stitch together disparate pieces of information to generate a potentially novel solution. He also highlights that prompt engineering will become the next “coding language” as so much of leveraging LLMs is knowing how to ask them the right questions. Additionally, Dr. Butte discusses how since 2016, UCSF has been working to deidentify its patient notes so that it can query them to answer clinical questions and ultimately enhance patient care. ⚡The need for patient-facing AI As patients are increasingly able to access their own personal health data in nicely structured formats (e.g., EHRs, wearables), they desperately need more tools to help them interpret and make decisions using that data. Dr. Butte understands that these patient-facing solutions are challenging to get funded but he emphasizes that patients need to receive the benefits of AI sooner. ⚡Evaluating healthcare AI solutions In order to evaluate AI solutions, we often put human specialists – such as medical professionals – on the same tasks. Understanding that specialists often disagree with each other, a significant challenge arises in figuring out how we can evaluate AI considering we can’t just “average” all the specialist opinions. Dr. Butte points out that there still remains a massive gap in AI evaluation tools. Additionally, there are so many organizations that want to have a say in how healthcare AI is regulated that the landscape is uncertain. An awesome conversation with an expert on all things AI meets healthcare. Listen to the full episode below: Spotify: https://spoti.fi/3Wr3643 Apple: https://apple.co/4acwgan

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I'm looking forward to speaking at this conference on the confluence of law, tech, advocacy and policy and how new innovation centers like the Berkeley Space Center can reinvent the way we tackle hard problems. Berkeley Center for Law and Business, #gobears

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People with high expectations have low resilience. Pain and suffering are the only way to teach you to be resilient. A good take from NVIDIA CEO and AI leader Jensen Huang Very relevant for a lot of startups discovering customers and generating revenue. #justdoit #resilience #success #leadership

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🤔 Curious about the Future of Work? Thrilled to host Matt Beane, professor at UCSB. Listen in as we discuss topics from his new book, "The Skill Code: How to Save Human Ability in an Age of Intelligent Machines," exploring how AI can be a partner to augment human skills, the role of digital apprenticeship in practical skill development, and the nuanced challenges of technology integration that benefit experts but may inadvertently impact novices.

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This is an important point. The ethic that we should build all possible technology “because we can” and “because it’s profitable” and “because someone else will“ has become pervasive and socially destructive. It is not unlike the wave of offshore manufacturing that hollowed out middle America and delivered up ghost towns and opioids and our current political disaster. Not sure what the answer is, but it is pretty clear the road we’re on risks going right over the cliff to techno-authoritarianism. (https://lnkd.in/ehi8QBqk) I'm exploring these issues and working toward a more constructive set of solutions on my substack: Reinventing Capitalism (https://lnkd.in/ewaaEcaA). It seems clear to me that new solutions are needed. Blindly following the techno-utopians to wave upon wave of new "solutions" that leave out humans seems to be a grave error. We need to re-think the structure of incentives in our society and encourage our best minds to develop technology to advance humanity, not replace it.

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Among the AI wars taking place right now (e.g. GPU rich v poor, Data quality), a war over margins is one of them. Daniel Gross compared NVIDIA's healthy 85%+ margins to a 'kind of interchange rate for tokens', and that all layers of the AI stack are incentivised to invest and architect their infrastructure to lower their interchange rate. One of the key incentives at work is to commoditise the cost of complements. This has been the impetus for PyTorch, TensorFlow, Android and now Llama for Meta. We can see this at work in high resolution with Snowflake launching Arctic and Databricks launching DBRX. As Apoorv A. wrote in his excellent piece last week, at this point in time value has disproportionately accrued to Semis and Infra, but if mobile and cloud are any indication then this will invert eventually and margins will expand for applications closest to the end consumers. They'll be helped by Wright's law, which is driving down the cost of every generation of frontier models within months of its release. The cutting edge will remain the province of a handful of companies, but the capabilities are diffusing at unprecedented rates. Application builders can unlock 10x better experiences at diluted margins by leveraging expensive SOTA models, before graduating to higher margins as inference costs inevitably collapse. We're still in the early innings, but the incentive to commoditise complements and the margin wars at large will continue to develop.

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"Microsoft Corp.’s earnings were “solid in so many ways,” in the view of Melius Research analyst Ben Reitzes. And they’re poised to get a lot better for a number of reasons, he argued in a note Friday. For one, the company’s Azure cloud-computing business hasn’t had quite enough capacity to meet booming artificial-intelligence demand. Additionally, the company has only just begun to recognize financial benefits from its Copilot AI software features. Microsoft MSFT, +1.82% grew the Azure business at a 31% clip last quarter, and AI contributed 7% to that growth — up from 6% of AI contributions in the December quarter. And given capacity constraints, the contributions Microsoft just posted “could have been even better,” Reitzes wrote. “This growth backs the ‘AI Gold Rush’ we are seeing with staggering [capital-expenditure] figures and spending outlooks from the first big three clouds that have reported this week,” he wrote. “Microsoft seems to have an edge right now, growing the fastest on a huge revenue base — working through various constraints pretty darn well.”"

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We're thrilled to announce M12's participation in DatologyAI's Series A! Datology is a leading data curation platform that empowers businesses to unlock the true potential of their data for AI and machine learning initiatives. As the field of AI continues to evolve, data curation will play an increasingly critical role. We believe Datology is at the forefront of this revolution, providing the tools and expertise necessary to build robust, reliable, and impactful AI models. We're already seeing SLM (small language models), including Microsoft phi-2, tout "data curation" as a major driver of improved model performance and accuracy. It's no secret that clean, curated data is the fuel for high-performing AI models. However, the status quo is to throw (big) data at the problem. Datology re-imagines how models are pre-trained by shifting the focus from parameters to data quality and data accuracy at the data curation phase. While we think big data will remain the foundation, we also believe curated, contextualized data will drive the next frontier of AI advancement. Congrats Ari Morcos Bogdan Gaza Matthew Leavitt! M12, Microsoft's Venture Fund Michelle Gonzalez Michael Stewart Todd Graham Peter B. Tina McNulty Valentina Escudero Jose Clautier Noah Bradford #data #microsoft

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📖excellent example of technical storytelling: making a complicated technical topic more understandable to general audience This informative story will help you understand 💡 what is Small Language Model 💡 why SLMs are valuable - increase options and practical use cases such as running a model on device and lower computing cost 💡 stories of Microsoft's research and engineering teams innovating to advance the state of the art in meaningful ways

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Generative agents are the next frontier for AI. But what are the most promising applications for this technology? In my conversation with Joon Sung Park, co-author of the landmark paper, “Generative Agents: Interactive Simulacra of Human Behavior,” he shared his perspective. He makes a case for founders to focus on soft-edged problems rather than hard-edged ones. "Soft-edged problems are where we can increasingly hill-climb toward being better. At a certain level, the technology starts to actually become useful."

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🌟Innovative VC Firm Overcomes Exits Drought with Secondary Sales🌟 ⛵Navigating a challenging landscape where exits are scarce, Santa Barbara Venture Partners (SBVP) has pioneered a novel approach to sustain its growth and attract investors for its second fund: secondary sales. Instead of waiting for traditional exits like IPOs or acquisitions, SBVP opted to sell shares of its portfolio companies, demonstrating its ability to generate returns for investors and stand out in a competitive market. 🎤According to Dan Engel, founder and managing partner of SBVP, these secondary transactions have been a game-changer, sparking investor interest and bolstering the firm's credibility. By leveraging its recent successes, including a lucrative stake in sports-betting company DraftKings Inc.' acquisition of digital lottery app Jackpocket, SBVP seized the opportunity to return profits to its limited partners (LPs) and pave the way for its second fund. 💡Engel highlighted the challenges faced by young VC firms in raising subsequent funds, particularly amid a downturn in exit activity and heightened investor scrutiny. With traditional exit routes becoming increasingly elusive, the pressure is on for firms to demonstrate tangible returns and establish a track record of success. ✨"For us, secondary sales have been a game-changer. They've helped us return profits to our LPs and attract investors for our second fund," said Dan Engel. 💰For SBVP, the decision to pursue secondary sales was driven by the need to provide liquidity to LPs and validate its investment thesis in the eyes of prospective investors. By strategically offloading portions of its holdings in high-performing portfolio companies like Bark Technologies and Rad AI, SBVP not only generated substantial returns but also bolstered investor confidence in its ability to deliver results. ⚠Despite the complexities and potential stigma associated with early share sales, Engel emphasized the importance of prioritizing investor returns and seizing opportunities to unlock value for stakeholders. With a focus on profitability and transparency, SBVP remains committed to its mission of delivering sustainable growth and maximizing returns for its LPs. 🔍 "Returning profits to our investors is our top priority. By strategically selling shares, we're proving our commitment to delivering results and driving value for our stakeholders," added Engel. As SBVP continues to explore secondary transactions and expand its investor base, the firm stands as a testament to innovation and resilience in the face of market challenges. 🚀 ✅ Looking to raise capital for your #fund and increase the international pool of your LP #investors?   🤝 Need warm #LP introductions?   📝 Selling #secondaries to increase liquidity?   🧐 Looking for co-investments?   ▶ G+QUANT's link for inquiries and fund decks: https://lnkd.in/gjC_EuTE #VCInnovation #SecondarySalesSuccess #InvestorReturns #ValueCreation 

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If you can find a way to push through the Valley of the Shadow of Death….there’s always success on the other side. But many give up before they hit their breakthrough!! I hear many entrepreneurs and investors say that “You need to know when to give up.” I say never give up!!!!!!!!! But you also need to understand how to LEARN as quickly as possible so that you can evolve (even sometimes pivot) before you run out of MONEY!!!! It’s all about learning and putting those learnings into practice as fast as possible. If startups had an infinite amount of runway every company would be successful because you could take as much time as you need to figure things out. Since time is limited for all startups, the race you have to win is the race against time. And time is directly correlated to runway. The best companies in the world 🌎 are the ones that LEARN faster than anyone (which is a direct corollary to failing fast) and put those learnings to Practice relentlessly. Thanks to AFROTECH for the support!!!

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🧱 Generative AI: A Paradigm Shift in Technology Generative AI is exploding, attracting massive investment as foundational models are seen as paradigm-shifting technologies. In 2023, global funding for generative AI companies increased nearly 4x year-over-year to over $28B across 700+ deals, with more than 60% concentrated in just the top 5 deals developing frontier AI models. Why the intense focus on foundational models? These powerful natural language, vision, and multimodal AI systems unlock vast possibilities — boosting content creation, analysis, scientific discovery, and more. While still nascent, they are expected to increasingly underpin real-world AI applications across industries in the coming years. Personally, I find it fascinating to witness this rapid evolution. Looking ahead 2-3 years, we'll see rapid advances in: ✅ Capabilities to handle ever more complex tasks ✅ Seamless multimodal integration (text, vision, audio) ✅ Improved safety and robustness ✅ Specialized models for targeted use cases ✅ Broader deployment across diverse industries and real-world scenarios As Albert Einstein once said, "Imagination is more important than knowledge". The generative AI revolution embodies this spirit, continuously pushing the boundaries of what’s possible, reshaping how we innovate and collaborate. Market Insights Credits: #SapphireVentures #VatianVentures #GenerativeAI #AI #TechInnovation #Investment #FutureTech

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UPDATE on #AI Explainabilty. SPOILER ALERT: Someone has some explaining to do! Q: "...is that a fair statement; that we don't understand how the models are working?" (Peter H. Diamandis - 7min in video). A: "Yeah..." (Nat Friedman) A: "Yeah.." (Emad Mostaque) The C-suite and boardroom must perk-up when top AI tech leaders along with the Oracle of Omaha (#WarrenBuffet in The Wall Street Journal) from completely different perspectives, the urgency for #AI prudent risk management. The good news, Warren says "the genie's only half out of the bottle...". Digital Directors Network X-Analytics (SSIC) NACD (National Association of Corporate Directors) #CyberROI #corpgov #AIsafety #AIexplainability #QTE

#AI is both over-hyped and under-hyped. Over-hyped in the sense that I don't believe artificial general intelligence (AGI) is imminent. Yann LeCun had a great interview in Wired where he outlined why (and dropped a great quote - "Machine Learning Sucks"). https://lnkd.in/exv35XGT Under-hyped in the sense that ROI is already hiding within existing business processes - someone just needs to do the work of re-thinking, re-designing and re-building with an AI first mindset. Friday, April 19th at 11:30am, join me at the River Club (https://lnkd.in/evs8XsYB) with the First Coast Tiger Bay Club for lunch, a short presentation and some q&a. To RSVP, email fctigerbay@gmail.com. The event is open to everyone, and $35 for lunch for non-members. Socrates Rivers

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Ilya Strebulaev and Andrew Ng recently led NACD Northern California’s inaugural Women Tech Directors event on AI and Innovation. We had the honor of hearing their expert views on what essential steps to take as a board director to adopt a venture capitalist mindset and leverage the power of AI strategically. Read the full article here: https://lnkd.in/gTfB22Fm Read the key takeaways below: 💡 Venture Mindset Principles 💡 ☑ Long-Term Views and Metrics: Shift the boardroom focus from short-term to long-term results. Emphasize forward-looking signals like customer lifetime value. Encourage a culture of long-term thinking and align incentives for executives accordingly. Ask questions about the company’s five-year focus and goals and consider a “premortem” exercise. ☑ Innovation and Leadership: Bet on the jockey, not on the horse—back founders even if they’ve experienced failure. Consider the “super founder”—the visionary leader driving projects forward—and ensure they receive the support they need to succeed. ☑ Strategic Decision-Making: Develop criteria for when to pull the plug on projects that aren’t working. Elevate strategic conversations by asking the right questions and challenging assumptions. Look at the same metrics year-over-year and not the data that makes a project look successful. ☑ Investment Strategy: Understand the psychology of investment decisions. Recognize the tendency for escalation of commitment and implement mechanisms to prevent biased decision-making. 💡AI in the Workplace 💡 ☑ Task-Based Analysis: Evaluate job roles based on tasks rather than entire positions. Identify opportunities for AI to automate repetitive tasks to enhance productivity without displacing jobs entirely. Tailor AI solutions to specific business needs for maximum impact. ☑ Risk Management: Address fears and concerns surrounding AI by implementing a strategic risk-management approach. There is too much time wasted worrying about AI risks and not enough focus on the potential opportunities—the risks are usually less than you think. Companies should strive for flexibility over commitment when investing in AI to adapt to rapidly changing technologies. ☑ Talent Acquisition and Education: Bridge the talent gap by systematically building a high-caliber team with expertise in AI—look at businesses that have previously failed for untapped talent. Leverage relationships to recruit top talent and invest in board education to ensure members are equipped to navigate AI-related decisions. ☑ Governance in AI: Implement governance structures that focus on the application of AI rather than the technology itself. Thank you to our partner Andrea Schulz at Grant Thornton LLP (US) for generously hosting this event and to NACD Northern California’s board chair Claudia Fan Munce for wonderfully moderating. #innovation #ai #NACD #boardofdirectors

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Exciting news! From the White House: "Microsoft will invest $3.3 billion in a new datacenter. Microsoft is committed to creating good-paying jobs with growth pathways and comprehensive benefits such as paid family leave. Microsoft will pair its datacenter investment with a commitment to investing in innovation and workforce in Racine and statewide. Microsoft will partner with Gateway Technical College to develop a Datacenter Academy that trains 1,000 Wisconsinites for datacenter and STEM roles by 2030, and will employ up to 2,000 people in permanent roles at its Racine facility. And, Microsoft will build a Co-Innovation Lab in southeast Wisconsin, as well as team up with the startup accelerator Gener8tor to train 1,000 business leaders to adopt AI in their operations, so that Wisconsin manufacturers can seize AI’s promise. Together, these investments will position the industrial heartland to lead the way in industries of the future."

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Falkonry (Suhas Mehta and Ashis Khan) and iba AG (Eric Snyder) will present how steel makers are pivoting to AI & Data driven decision support system at AISTech 2024 today (May 6, 2024) - please join us if you are interested. I co-authored this paper with Eric Snyder of iba AG.

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