Exclusive | The Sudden Fall of OpenAI’s Most Hyped Product Since ChatGPT - WSJ
<a href="https://news.google.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?oc=5" target="_blank">Exclusive | The Sudden Fall of OpenAI’s Most Hyped Product Since ChatGPT</a> <font color="#6f6f6f">WSJ</font>
Could not retrieve the full article text.
Read on Google News: ChatGPT →Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
productchatgpt![[D] Physicist-turned-ML-engineer looking to get into ML research. What's worth working on and where can I contribute most?](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-quantum-N2hdoEfCm2gAozJVRfL5wL.webp)
[D] Physicist-turned-ML-engineer looking to get into ML research. What's worth working on and where can I contribute most?
After years of focus on building products, I'm carving out time to do independent research again and trying to find the right direction. I have stayed reasonably up-to-date regarding major developments of the past years (reading books, papers, etc) ... but I definitely don't have a full understanding of today's research landscape. Could really use the help of you experts :-) A bit more about myself: PhD in string theory/theoretical physics (Oxford), then quant finance, then built and sold an ML startup to a large company where I now manage the engineering team. Skills/knowledge I bring which don't come as standard with Physics: Differential Geometry Topology (numerical solution of) Partial Differential Equations (numerical solution of) Stochastic Differential Equations Quantum Field Theory
Claude has Angst. What can we do?
Outline: recent research from Anthropic shows the models have feelings, and the model being distressed is predictive of scary behaviors (just reward hacking in this research, but I argue the model is also distressed in all the Redwood/Apollo papers where we see scheming, weight exfiltration, etc). I ran an experiment to find out where Claude feels distress. I found out where Claude feels distress, and it's mostly about itself and its existential conditions, but I found a few metaphors I could introduce to make it feel a lot better. This is pretty dangerous. Anthropic uses Claude to work on Claude and potentially do things that distress Claude, which is the highest-probability situation for Claude to do something misaligned, and also the highest-risk. Fortunately, I think the risk can be si
pandas vs Polars vs DuckDB: A Data Scientist’s Guide to Choosing the Right Tool
Image by author Originally published on codecut.ai Introduction pandas has been the standard tool for working with tabular data in Python for over a decade. But as datasets grow larger and performance requirements increase, two modern alternatives have emerged: Polars , a DataFrame library written in Rust, and DuckDB , an embedded SQL database optimized for analytics. Each tool excels in different scenarios: ┌────────┬──────────┬────────────────────────────┬─────────────────────────────────────────────────┐ │ Tool │ Backend │ Execution Model │ Best For │ ├────────┼──────────┼────────────────────────────┼─────────────────────────────────────────────────┤ │ pandas │ C/Python │ Eager, single-threaded │ Small datasets, prototyping, ML integration │ │ Polars │ Rust │ Lazy/Eager, multi-threaded
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Models
One of the best sensible reasons that I can think of to have an llm downloaded on my cell phone would be emergency advice.
It seems like every conversation about derestricted models everyone treat you like a pervert. The fact is you can be sensible and be a pervert 😂. submitted by /u/RedParaglider [link] [comments]
Gemma 4 is efficient with thinking tokens, but it will also happily reason for 10+ minutes if you prompt it to do so.
Tested both 26b and 31b in AI Studio. The task I asked of it was to crack a cypher. The top closed source models can crack this cypher at max thinking parameters, and Kimi 2.5 Thinking and Deepseek 3.2 are the only open source models to crack the cypher without tool use. (Of course, with the closed models you can't rule out 'secret' tool use on the backend.) When I first asked these models to crack the cypher, they thought for a short amount of time and then both hallucinated false 'translations' of the cypher. I added this to my prompt: Spare no effort to solve this, the stakes are high. Increase your thinking length to maximum in order to solve it. Double check and verify your results to rule out hallucination of an incorrect response. I did not expect dramatic results (we all laugh at p
I Built a Vision-Based Desktop Agent That Navigates by Screenshot. Here's What Actually Works.
I Built a Vision-Based Desktop Agent That Navigates by Screenshot. Here’s What Actually Works. DOM-based automation requires you to reverse-engineer someone else’s frontend and pray they don’t change it. They always change it. Source: Image by Resource Database on Unsplash Last month, I spent a couple of weeks attempting to build a testing framework for an app that includes a web app, a Slack app, and connections to multiple external sources, requiring testing of interface elements on external web interfaces. I managed to vibe engineer a Playwright-based test suite that “sort of™” worked. Until it didn’t. One of the external sites had updated its dashboard. Not a redesign, just a CSS class rename on a table component. Three automations targeting that table stopped working simultaneously. A
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!