AI - Ongoing Model Improvements
Mickey Schafer
Jul 4
This past semester, a student of mine despaired over analyzing a 20+ question survey with 92 responses. She uploaded the spreadsheet to NotebookLM, a tool we'd used in class, which not only cheerfully assured her it would do the task, but also returned basic R values with short statements about strong relationships. She was deli... See more
Jul 4
This past semester, a student of mine despaired over analyzing a 20+ question survey with 92 responses. She uploaded the spreadsheet to NotebookLM, a tool we'd used in class, which not only cheerfully assured her it would do the task, but also returned basic R values with short statements about strong relationships. She was deli... See more
Ethan Mollick • Gradually, then Suddenly: Upon the Threshold
The incentive to find breakthrough science that provides a performance pathway other than scaling is increasing. A GPT-6 class model will cost $10 billion and three years to improve on GPT-5 by some uncertain degree. That’s a ton of time and a lot of cash for an uncertain payout: in other words, a substantial prize for anyone who can figure out pro... See more
Azeem Azhar • 🧠 AI’s $100bn question: The scaling ceiling
While LLMs continue to devour web-scraped data, they’ll increasingly consume their own digital progeny as AI-generated content continues to flood the internet. This recursive loop, experimentally confirmed, erodes the true data landscape. Rare events vanish first. Models churn out likely sequences from the original pool while injecting their own un... See more
Azeem Azhar • 🔮 Open-source AI surge; UBI surprises; AI eats itself; Murdoch’s empire drama & the internet’s Balkanisation ++ #484
o, alternative pathways to building Type-2 reasoning-capable AI systems, likely using neurosymbolic approaches, have become much more attractive. People like Gary Marcus have argued for neurosymbolic approaches for decades. Such approaches combine the pattern recognition of neural nets, like LLMs, with symbolic reasoning’s logic and rules. Vinod Kh... See more
Azeem Azhar • 🧠 AI’s $100bn question: The scaling ceiling
As Ethan said a year ago, it takes 10 hours of monkeying around to get into it. But I think a good AI executive training program can dramatically shorten the window, assuming a growth mindset on the exec’s part. I ran into a retired architect the other day who was bemoaning wanting to work in retirement but he had never learned CAD-CAM! Now he’s tw... See more
Ethan Mollick • Gradually, then Suddenly: Upon the Threshold
Arbituram
Jul 4
Same here; I'm not rubbishing the benchmarks, they have their uses, but Sonnet 3.5 just *feels* so far ahead of anything else, I had to go for a long walk on the beach after using it to contemplate how long humanity has left.
Sonnet 3.5 is able to have thoughtful and nuanced conversations on complex topics and to be proactive in codin... See more
Jul 4
Same here; I'm not rubbishing the benchmarks, they have their uses, but Sonnet 3.5 just *feels* so far ahead of anything else, I had to go for a long walk on the beach after using it to contemplate how long humanity has left.
Sonnet 3.5 is able to have thoughtful and nuanced conversations on complex topics and to be proactive in codin... See more
Ethan Mollick • Gradually, then Suddenly: Upon the Threshold
This is all early, and based on first impressions, but I think that voice capabilities like GPT-4o’s are going to change how most people interact with AI systems. Voice and visual interactions are more natural than text and will have broader appeal to a wider audience. The future will involve talking to AI.
Ethan Mollick • On speaking to AI
GPT-4 and 4-Turbo have always been available for free in Microsoft Copilot. 4o is now free in ChatGPT. Claude 3.5 Sonnet is now free in Claude. So there are many that have never subscribed to a premium plan that have been using the best models all along still
Ethan Mollick • Gradually, then Suddenly: Upon the Threshold
it is kind of surprising that none of the major AI labs seem to have put out any deep documentation aimed at non-specialists. There are some guides for programmers or serious prompt engineers, but remarkably little aimed at non-technical folks who actually want to use these systems to do stuff - the vast majority of users
Ethan Mollick • Confronting Impossible Futures
LeCun points to four essential characteristics of human intelligence that current AI systems, including LLMs, can’t replicate: reasoning, planning, persistent memory, and understanding the physical world. He stresses that LLMs’ reliance on textual data severely limits their understanding of reality: “We’re easily fooled into thinking they are intel... See more