John Menadue’s Post

Continuing with the third installment of “Getting to Know the DeepJudge Team.” In this edition, meet Kevin Roth, Co-Founder and COO. Read how he turned from theoretical physics to machine learning, and how he thinks the legal industry was predestined for transformation by artificial intelligence. Read the full interview here: https://lnkd.in/dgZDRN5t

I am excited to share a thought-provoking blog post titled "Turing Kicked Us Out of Heaven." This article delves into the profound implications of Turing's work and its influence on the trajectory of artificial intelligence, exploring both the opportunities and challenges that arise from our relationship with technology. It's a must-read for anyone interested in the intersection of computer science and the human experience. Dive into the discussion and discover insights that could reshape your understanding of AI's place in our world. You can read the full post here: https://ift.tt/zGiLx2u

“ Here is one narrow way to look at human history: after thousands of years of compounding scientific discovery and technological progress, we have figured out how to melt sand, add some impurities, arrange it with astonishing precision at extraordinarily tiny scale into computer chips, run energy through it, and end up with systems capable of creating increasingly capable artificial intelligence. This may turn out to be the most consequential fact about all of history so far. It is possible that we will have superintelligence in a few thousand days (!); it may take longer, but I’m confident we’ll get there. How did we get to the doorstep of the next leap in prosperity?” - from the article Very interesting article 👇🏻

Is the future of computer science and AI going to be just like Star Trek? 🌟 Experts from the likes of Loughborough University, MIT, and Yale say we are set to see the emergence of ‘Collective AI’, where numerous units form a network to share information with each other. However, unlike many sci-fi narratives, the computer scientists envision Collective AI will lead to major positive breakthroughs across various fields! Delve deeper here: https://bit.ly/49g33e9 #StarTrek #CollectiveAI #ComputerScience

For deep tech enthusiasts like me, Alan Kay’s 1982 quip still rings true: “People who are really serious about software should make their own hardware.” This principle is core to Cerebras Systems’ approach. From day one, they've embraced hardware-software co-design, crafting their systems to address the unique demands of large-scale neural networks. Sean Lie, co-founder and CTO, explains why this holistic strategy is more than just an engineering choice. It’s the path to the next big leap in AI’s capabilities. Our full conversation here: https://lnkd.in/gWZCi4zE

Most mechanistic interpretability work has been motivated by AI safety concerns, but could interpretability also drive scientific discovery? Goodfire's CTO Daniel Balsam & CSO Tom McGrath think so! 🔥 "We've got scientific foundation models like AlphaFold, ESM3, models of quantum chemistry, weather prediction – it's a huge list and it's growing all the time. When models are better at scientific predictions than our best theories, they probably know something we don't. If we're capable of explaining models, anything you can train a model to do, you can explain. So I think this has the potential to be a core transformative scientific technology, to go into these scientific models and pull out the new science and then bring it back to the rest of the world." (Link to full episode in comments👇)

Amazing Article from our very own Magda Domagała "The dynamic interplay first brought about by the web and social, then evolved by AI and spatial computing, has not only democratised fandom, but has also blurred the lines between reality and fiction, giving rise to more interconnected and personally resonant relationships between fans and the characters that define the cultural landscape." Have a read: https://lnkd.in/ep6D4Qu7

How am I only reading about Meredith Whittaker, President of Signal Messenger today? I don't know, but wow - what a beacon of hope for ethical use of #data and #artificialintelligence. "Make no mistake – I am optimistic – but my optimism is an invitation to analysis and action, not a ticket to complacency... ...What we call AI today grew out of this toxic model–and must be understood primarily as a way of marketing the derivatives of mass surveillance and concentrated platform and computational power. Currently, there are only a small handful of firms–based in the US and China–who have the resources to create and deploy large-scale AI from start to finish. These are the cloud and platform monopolies–those that established themselves early on the backs of the surveillance business model. Everyone else is licensing infrastructure, scrambling for data, and struggling to find market fit without massive cloud infrastructures through which AI can be licensed to customers or massive platforms into which AI can be integrated as a feature or service touching billions of people. This is why even the most successful AI ‘startups’ – Open AI, Mistral, Inflection – are ultimately ending up as barnacles on the hull of the Big Tech ship–the Microsoft ship, in their case. It’s why Anthropic needs to be understood as a kind of subsidiary of Google and Amazon." If you too are worried about the influence of the hyperscalers on our destiny, her award speech attached below is a must read. Here is also a recently published interview with her by Madhumita Murgia of the Financial Times - Signal’s Meredith Whittaker: ‘I see AI as born out of surveillance’ - https://on.ft.com/4en3WVF via @FT

As we approach #PRW2024, we're looking back at our webinar from last year's Peer Review Week, where Mads Rydahl—an AI innovator behind Siri, UNSILO, and paperflow.аi—challenged the prevailing approaches to peer review and preprints. 🗣️ "The publishers today are speaking in tongues," he pointed out, highlighting the contradictory messages about preprints and peer-reviewed research. Mads advocated for a faster, more collaborative model that matches the pace of discovery in fields like computer science. Now, a year later, have we moved closer to the open and agile research communication he envisioned? 🎥 Watch the full webinar here: https://lnkd.in/dMKxKcvE

Our Pattern Fellows Program was fortunate to learn all about artificial intelligence last week. We had amazing guest speakers, including Andrew Sica, a senior technical staff member working on AI at IBM; Brad Johnsmeyer from Ecohome; and Jason Scott, who was a founding member of the AI practice in the law firm of Gordon Rees Scully Mansukhani. We learned about the broad applicability of artificial intelligence, emerging uses across industry sectors, and some of the sticky legal and practical questions that are still to be answered. I'll be the first one to admit holes in my knowledge game - this is moving faster and farther than I realized!