AI - Ongoing Model Improvements
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... See more
Azeem Azhar • 🔮 Open-source AI surge; UBI surprises; AI eats itself; Murdoch’s empire drama & the internet’s Balkanisation ++ #484
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... See more
Ethan Mollick • Gradually, then Suddenly: Upon the Threshold
I still think that we are thinking about scaling of network-based intelligence looking at this particular network. An extended network of machines and humans in larger networks facilitated by smaller and increasingly embodied devices might in themselves add an AI-augmented neocortex to our (human-machine) systems. Intelligence will continue to... See more
Azeem Azhar • 🧠 AI’s $100bn question: The scaling ceiling
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
I isn’t ready to be an entrepreneur, but its ideation-prototype-interview cycle does in a couple of seconds what takes my students months to do. AI isn’t ready to build educational games without errors, but it is able to instantly make an interactive simulation that explains a difficult concept, even if some nuance is missing
Ethan Mollick • Confronting Impossible Futures
But there's just something about the immediacy and interactivity of Claude's "Artifacts" window, combined with the model's less stilted tone that brings it home.
For the most avarege users, these seemingly minor difference matter so much more than raw performance on abstract LLM benchmarks.
For the most avarege users, these seemingly minor difference matter so much more than raw performance on abstract LLM benchmarks.
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... 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... See more
Ethan Mollick • Gradually, then Suddenly: Upon the Threshold
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... See more
Azeem Azhar • 🧠 AI’s $100bn question: The scaling ceiling
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... 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... See more