There’s a lot of excitement about what AI (specifically the latest wave of LLM-anchored AI) can do,
and how AI-first companies are different from the prior generations of companies.
There are a lot of important and real opportunities at hand, but I find that many of these conversations
occur at such an abstract altitude that they border on meaningless.
Sort of like saying that your company could be much better if you merely adopted more software. That’s certainly true,
but it’s not a particularly helpful claim.
On the ProjectVRM list, John Wunderlich shared a find that makes clear how advanced and widespread AI-based shopping recommendation has gone so far (and not just with ChatGPT and Amazon). Here it is: Envisioning Recommendations on an LLM-Based Agent Platform: Can LLM-based agents take recommender systems to the next level? It's by Jizhi Zhang, Keqin Bao, Wenjie…
Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task – MIT Media Lab
This study explores the neural and behavioral consequences of LLM-assisted essay writing. Participants were divided into three groups: LLM, Search Engine…
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How to Partner with Your LLM for Deeper Coding Challenges
Introduction With the rise of "vibe-coding," it's easy to forget that LLMs offer much more than just code generation. Their real strength lies in language.
The hype about the potentials (it’s always future potential, never real current use) of AI has discarded its last cycle (“reasoning models”/”deep research”, both terms being factually untrue and deeply deceiving at best) and moved to a new double whammy of “agentic AI” and “Vibe Coding”. Now “agentic AI” basically just means that some LLM […]
Ash AI: A comprehensive LLM toolbox for Ash Framework
Ash AI is a new extension for Ash Framework, enabling LLM integration for Elixir apps. Use Ash's declarative approach to take advantage of structured outputs, secure tool calling and to build MCP servers with ease.
Recommended Hardware for Running LLMs Locally - GeeksforGeeks
Your All-in-One Learning Portal: GeeksforGeeks is a comprehensive educational platform that empowers learners across domains-spanning computer science and programming, school education, upskilling, commerce, software tools, competitive exams, and more.
The landscape of Large Language Models (LLMs) is evolving rapidly, with powerful and open models being released at an unprecedented pace. As these technologies advance, so does the potential to integrate them into our existing systems. Traditionally, we've built systems with distinct layers such as the Application layer and Data Persistence layer.
LLMs and Vibe Coding are there. But why? Because our tech is not that advanced and we're disempowered by it. Make tech not suck, and you'll need no LLMs.
Online discussions about using Large Language Models to help write code inevitably produce comments from developers who’s experiences have been disappointing. They often ask what they’re doing wrong—how come some …
[Simon Willison] has put together a list of how, exactly, one goes about using a large language models (LLM) to help write code. If you have wondered just what the workflow and techniques look like…