Tag: Rapamycin

(No paywall) A PhD student at Southern Methodist University lost a publishing deal reportedly worth more than $2 million last month after allegations he used AI to write parts of the book. The author, Jerry Falade, denied the claims in a social media post. “I’ll talk when the time is right,” Falade wrote. “Definitely innocent!!!” submitted by /u/Traditional_Figure70 [link] [comments]

I build CTRLpotato, so obvious disclosure first, all six products I tested are competitors. CTRLpotato isn't included in the results and I'm not using this to declare a winner. Over June and July I tested Cluely, Interview Coder, LockedIn AI, ULTRACODE, Parakeet AI and Final Round AI on Mac and/or Windows. I originally did this because I kept seeing claims like invisible, undetectable, real-time, etc. and wanted to see what the actual desktop apps did. I ended up with enough screenshots, recordings and notes that keeping everything in six separate reviews became pretty useless, so I normalized it into a dataset. It's now 66 assessments across 6 products and 11 criteria. A few results that surprised me: All 6 failed the focus-behavior check in the setup I tested. All 6 failed the cursor-behavior check. Shortcut isolation failed on all 5 products where I tested it. The sixth wasn't tested. I tested receiver-side screen sharing on 4 products. 2 failed and 2 were mixed. There were also some pretty strange context failures, where an assistant would answer an old coding task or otherwise lose track of what it was supposed to be answering. I don't want to oversell those numbers. This wasn't a lab experiment where every product got an identical setup. Different versions, platforms and test flows were involved, which is why every row includes the app version, platform, date, what actually happened, limitations and evidence where I have it. The five result labels are just passed, mixed, failed, not found and not tested. A failure means it failed in the documented setup, not that the feature can never work. The whole thing is public here: https://www.ctrlpotato.com/compare I also put the actual dataset on GitHub with CSV/JSON/JSONL, schema, codebook and checksums: https://github.com/ae0j/ctrlpotato-ai-interview-assistant-benchmark And there's a versioned Zenodo DOI if anyone wants to cite or archive it: https://doi.org/10.5281/zenodo.21915738 The dataset is free to use, including commercially, with attribution. One thing I'm still unsure about: whether the passed/mixed/failed column actually makes the dataset better. The more I worked on this, the more I felt that the raw observation + limitations were more useful than trying to compress what happened into one label. Curious what people who work with evaluation datasets think. submitted by /u/TheMaerty [link] [comments]

Part 1 of 3: Rather than producing jobs, the US economy actually lost 23,000 jobs in July, according to Bureau of Labor Statistics data released on Friday. In addition, May and June’s job numbers were revised downward, showing a combined 103,000 fewer jobs than previously reported. As if this weren’t bad enough, wage growth has also slowed. Average hourly earnings rose by just 0.1% from June. This isn’t just a single month’s slow wage growth, either. Average hourly earnings increased just 3.2% over the past year – the lowest annual growth rate in five years. What’s going on? It’s too early to tell. But evidence is mounting that artificial intelligence is playing a role. New research by economists at Morgan Stanley shows that the rate of unemployment is half a percentage point higher than it would otherwise be in occupations significantly exposed to AI, which they put at about 30% of all employment. The effect is even more dramatic among younger people. Workers in these exposed occupations are also finding it more difficult to transition from unemployment back into employment than workers in less exposed occupations, leading to longer spells of joblessness. And according to research by the economists Sania Edlich and Apollo Global Management’s Torsten Slok, wage growth in jobs exposed to AI has contracted by 6.7% since 2023. This slowdown in wage growth has already resulted in at least $28bn in losses for 5.8 million affected workers. From the end of the article: "Well, then, why can’t we stop the whole thing? Why can’t we decide that, to the vast majority of us, the incalculable costs and risks of AI aren’t worth the potential benefits?" submitted by /u/Silent-Resort-3076 [link] [comments]

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Hi everyone! I'm conducting this survey as part of my Master's thesis and would greatly appreciate your participation. The research examines how employees' perceptions of HR practices relate to work engagement and innovativeness, and how attitudes toward the application of Artificial Intelligence in the workplace influence these relationships. Who can participate? You are currently working in Germany (full-time or part-time). You are 18 years or older. The survey is anonymous, takes 5–7 minutes, and all responses will be used solely for academic research. 👉 Survey: https://pollmill.com/f/xya75pv.f Even if you don't actively use AI at work, your perspective is still valuable—the study focuses on employees' attitudes toward AI in the workplace, not their level of AI usage. Thank you for helping with my research! submitted by /u/miawallace1997 [link] [comments]

So it has been almost 4 years since the world saw its first glimpse of this so called "revolutionary" technology. So where are we with regards to building something profitable and long-lasting like computing was in the 70s . Is buu le inflating or deflating ? Also what is the overall strategy of AI honchos ? What is their long term vision ? Thanks submitted by /u/Loner_Indian [link] [comments]

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I thought this was an interesting example of how Japan is publicly framing data-center development. This is from an official Tsukuba City publication. (Translated via GPT Image 2.0, source images included) What stood out to me is how much space they devote not just to the economic benefits, but to the social contract around the project: noise, heat, electricity demand, groundwater, electromagnetic radiation, landscaping, setbacks from residential areas, disaster resilience, public facilities, community consultation, and even how residents’ concerns are supposed to be handled. Obviously, an official brochure is still an official brochure, so I wouldn’t treat every statement as proof that implementation will be perfect. But I also wouldn’t dismiss this as meaningless PR. In the Japanese municipal context, these are publicly attributable commitments. If the city or developer later behaves in a way that clearly contradicts what was presented to residents, that can become a reputational and political problem. So I think the useful way to read this is: not “every promise is guaranteed,” but “this is a fairly serious statement of what the project is expected to deliver and what standards residents can hold them to.” I find the contrast interesting because data-center discussions elsewhere often seem to start with capacity, investment, AI demand, and power procurement. Here, the public-facing explanation starts almost immediately with: How does this affect the people who already live here? submitted by /u/Top_Course_640 [link] [comments]