> Powered by > > @Scenario_gg > > We help creative teams orchestrate and scale everything they produce. > > Try it out today > > > — Emm | scenario.com
Source: https://x.com/emmanuel_2m/status/2107142680782438466
> Thanks to Bloomberg ( > > @business > > ) that covered what we’re launching today and the regulatory path that got us here. > > > (3/9) Until now, AI in healthcare has been limited to answering questions, summarising information, or assisting a clinician. We’ve seen a handful of organizations approved to refill prescriptions initially written by a human doctor with AI. > > Nolla is taking a big step further > > > (4/9) This is a huge breakthrough because healthcare has always had a fundamental constraint: > > People. > > There are only so many doctors and only so many hours in the day. For millions of Americans, that means they just never get the care they need. > > > (5/9) Every day, doctors across the U.S. spend hours treating routine, well-understood cases. That leaves less time for the complex, high-risk cases where their expertise is needed most. > > AI can make an enormous difference by taking on more of that routine care. > > > (6/9) We’re starting with acne care in Utah. > > ~100,000 Utahns have active acne. > > 90% of them have never seen a dermatologist. > > In a state with the highest melanoma incidence in the country, dermatologists are already stretched thin by routine cases AND still don’t have enough > > > — Luis Wenus
> Core runs local models 24/7 entirely on-device. No data ever leaves your home. > > Each core comes with: > - NVIDIA RTX PRO 4000 Blackwell SFF GPU > - 64GB DDR5 RAM > - 1TB NVMe M.2 SSD > - AMD Ryzen 5 7600 CPU > > > You connect and talk to Core through your laptop, mobile app, or iMessage. > > > Core has full context from all of your apps, files, and devices. > > It recognizes trends in sleep data from my Whoop and connects them to late meetings on my calendar, finding actionable ways to improve my sleep. > > > Core is a full computer - it has its own file system, browser, and tools to take action just as you would. > > It browses the web for the best moving companies in San Francisco, pulls their phone numbers, and calls them to find who's available for the lowest price. > > > You can use your Core to power inference in other apps and custom harnesses like OpenCode, OpenClaw, and Hermes. > > Core reaches over 87 tok/s on Qwen-3.8-27B and 32 tok/s on Qwen-3.8-Next. > > > — Zain Javaid
> ...𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐜𝐡𝐚𝐧𝐠𝐞 𝐭𝐡𝐚𝐭 𝐡𝐚𝐝 𝐭𝐚𝐤𝐞𝐧 𝐩𝐥𝐚𝐜𝐞 𝐨𝐧 𝐞𝐚𝐫𝐭𝐡. 𝐔𝐬𝐮𝐚𝐥𝐥𝐲 𝐭𝐡𝐞 𝐫𝐞𝐬𝐢𝐬𝐭𝐚𝐧𝐜𝐞 𝐜𝐚𝐦𝐞 𝐟𝐫𝐨𝐦 𝐭𝐡𝐨𝐬𝐞 𝐠𝐫𝐨𝐮𝐩𝐬 𝐰𝐡𝐨 𝐬𝐭𝐨𝐨𝐝 𝐭𝐨 𝐥𝐨𝐬𝐞 𝐢𝐧𝐟𝐥𝐮𝐞𝐧𝐜𝐞, 𝐬𝐭𝐚𝐭𝐮𝐬, 𝐦𝐨𝐧𝐞𝐲...𝐚𝐬 𝐚 𝐫𝐞𝐬𝐮𝐥𝐭 𝐨𝐟 𝐭𝐡𝐞 𝐜𝐡𝐚𝐧𝐠𝐞. 𝐀𝐥𝐭𝐡𝐨𝐮𝐠𝐡 𝐭𝐡𝐞𝐲 𝐧𝐞𝐯𝐞𝐫 𝐚𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐭𝐡𝐢𝐬 𝐚𝐬 𝐭𝐡𝐞𝐢𝐫 𝐫𝐞𝐚𝐬𝐨𝐧 𝐟𝐨𝐫 𝐫𝐞𝐬𝐢𝐬𝐭𝐢𝐧𝐠 𝐢𝐭. 𝐈𝐭 𝐰𝐚𝐬 𝐚𝐥𝐰𝐚𝐲𝐬 𝐭𝐡𝐞 𝐠𝐨𝐨𝐝 𝐨𝐟 𝐡𝐮𝐦𝐚𝐧𝐢𝐭𝐲 𝐭𝐡𝐚𝐭 𝐫𝐞𝐬𝐭𝐞𝐝 𝐮𝐩𝐨𝐧 𝐭𝐡𝐞𝐢𝐫 𝐡𝐞𝐚𝐫𝐭𝐬.” > > > — Pessimists Archive
Source: https://x.com/PessimistsArc/status/2107081120269439366
> People resist new technology, new ideas. As Dostoevsky opens Crime & Punishment with: "Taking a new step, uttering a new word, is what people fear most." I think fear points the way toward progress. Here's an ad from 1915 (via @PessimistsArc) suggesting a horse outperforms a car. > > — Lex Fridman
> On 400 claim-verification questions built from SEC filings, Jev tied GPT-6 Astra at 97.5% accuracy for ~$0.025 per 1,000 cases versus $12.29. > > It is also quite fast: at 32 judgments about one document, Jev’s median latency was 194x lower than Astra’s. > > > We did not see these gains carry over to legal reasoning. Jev ranked last on our 12-task LegalBench slice. When we tuned its confidence threshold for a 1% error budget, Jev automated 95% of held-out claim-verification cases—but at 1.6% error. > > > Despite speed and cost being high priority, task fit should come first. Strong results on one benchmark don’t guarantee reliable performance on your workload or that confidence threshold will hold up on unseen cases. > > For the full report, visit > > > — Vals AI
> ...professional work completely, bout about 90% they say. > > What a fantastic time to be alive. I love it. > > > https:// > > github.com/storytold/phot > > ocraft > > … (Photoshop) > > https:// > > github.com/storytold/vect > > orcraft > > … (Illustrator) > > https:// > > github.com/storytold/film > > craft > > … (Premiere) > > https:// > > github.com/storytold/ligh > > tcraft > > … (Lightroom) > > https:// > > github.com/storytold/prin > > tcraft > > … (Acrobat Pro) > > https:// > > github.com/storytold/effe > > ctcraft > > … (After Effects) > > https:// > > github.com/storytold/desi > > gncraft > > … (InDesign) > > > — Chubby
Source: https://x.com/kimmonismus/status/2107618163726921853
> ...nothing bad happens, and kind of figure out how to dole out the benefits.’” > > He calls that “a completely unacceptable tradeoff.” > > > — Chris
Source: https://x.com/ChrisGPT/status/2106873284113424574
> https://t.co/fJsAXXm4gO > > — Brendan Bordelon
Source: https://x.com/BrendanBordelon/status/2106852703842492511
> Replying to @brendanbordelon
> ...Its predicted ability to sort electrons by spin appears to have been hiding in plain sight for 27 years. > > > As far as we know, YBaMnFeO₅ is a new design that was never made or proposed as this kind of magnet. Simulations predict a 2.35 eV band gap and magnetism above room temperature, but the Mn/Fe checkerboard it needs may scramble during synthesis. > > KV[Cr(CN)₆] stays magnetic up to > > > These are predictions for perfect crystals; nobody has measured the spin sorting yet. The next step is to make KV[Cr(CN)₆] again and measure it. > > It is clear that models will begin to make huge strides in material science quite soon. > > The inputs, raw outputs and scripts behind > > > — Vals AI
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— Pessimists Archive
Source: https://x.com/PessimistsArc/status/2106808432330215744
> Our fits imply recent growth of about 1.8× per month at the median and 2.2× at the 90th percentile, or doubling times of 34 and 27 days, respectively. > > As of mid-August, daily usage was valued at around $600 for median researchers, and over $7,000 for the 90th percentile. > > > These figures value usage at API prices, so they don’t measure OpenAI’s actual costs. Early growth partly reflects more researchers adopting agents, in addition to existing researchers using agents more intensely. > > See more on our site: > > > — Epoch AI
Source: https://x.com/EpochAIResearch/status/2107174397698289762