“OpenAI published only 151 cases but appears in 500 implementations (3.3x multiplier through Azure).”

“As context lengths move into tens and hundreds of thousands of tokens, the key value cache in transformer decoders becomes a primary deployment bottleneck.”

“The model struggled to write unit tests for a simple function called interval2short() that just formats a time interval as a short, approximate string... It really struggled to identify that the output is "2h 0m" instead of "2h." ... It then went on a multi-thousand-token thinking bender before deciding that it was very important to document that interval2short() always returns two components.”

““Hello, I am a practicing physician and and only have a novice understanding of programming... At this point, I’m already saving at least a thousand dollars a year by not having to buy an AI scribe, and I can customize it as much as I want for my use case. I just wanted to share because it feels like an exciting time and I am bewildered at how much someone can do even just in a weekend!””

“The user's frustration is evident in their statement: "How is it possible that chatGPT still fails at simple Excel formulas, yet can produce thousands of lines of Python code without mistakes?"”

“The conditional entropy or code length in many cases continues to decrease with context length at least to $N\sim 10^4$ characters, implying that there are direct dependencies or interactions across these distances.”

“Preguss enables highly automated RTE-freeness verification for real-world programs with over a thousand LoC, with a reduction of 80.6%~88.9% human verification effort.”

“We’re in the midst of a global mental-­health crisis.”

“Online methods can achieve an average success rate of 45/19/77% with just a few thousand queries over three tasks where static methods from existing multi-turn conversation benchmarks find few or even no failure cases.”

“Conversations still seem to break down once you get into the hundreds of thousands of tokens.”

“SLIM-Brain establishes new state-of-the-art performance on diverse tasks, while requiring only 4 thousand pre-training sessions and approximately 30% of GPU memory comparing to traditional voxel-level methods.”

“"LLM companies should not be able to so easily extinguish thousands upon thousands of high-value claims at bargain-basement rates."”

“It studies how systems evolve over time and reduces thousands of variables into compact equations that still capture real behavior.”

“AstraZeneca’s AI is already embedded in national healthcare systems, screening hundreds of thousands of patients and demonstrating what happens when AI […]”

“Its tiny single-chip design packs tens of thousands of electrodes and supports advanced AI models for decoding movement, perception, and intent.”

“Clinical Coding is the technology that converts information from medical records regarding a patient's condition, diagnosis, treatment, etc., into codes of some standard classification system. In Japan, for diseases, it is mostly converted to ICD-10 (International Classification of Diseases, 10th edition), and for procedures, it is converted to codes from the medical treatment behavior master. This task is characterized by a very large number of classes, a significant bias in class occurrence rates (rare diseases occur in about one in several hundred thousand people), and...”

“Thousands of merged AI-generated pull requests and the future of large-scale software maintenance.”

“Behind every impressive AI system are thousands of real humans providing crucial data, feedback, and expertise.”

“”

“Imagine supercomputers that think with light instead of electricity. That s the breakthrough two European research teams have made, demonstrating how intense laser pulses through ultra-thin glass fibers can perform AI-like computations thousands of times faster than traditional electronics.”

“The article doesn't contain a direct quote.”

“”

“We're obsessed with generating thousands of tokens a second for a reason.”

“We’ve had ChatGPT for 18 months, but what’s it for? What are the use-cases? Why isn’t it useful for everyone, right now? Do Large Language Models become universal tools that can do ‘any’ task, or do we wrap them in single-purpose apps, and build thousands of new companies around that?”

“The article likely includes a quote from a Google representative or a Hugging Face representative, possibly discussing the benefits of the integration or the ease of use of the models.”

“Upgrading early warning systems to make accurate and timely information accessible to these populations can save thousands of lives per year.”

“The model is an 11-billion parameter T5-derivative that has been fine-tuned on feedback given on hundreds of thousands of searches done (anonymously) on our platform.”

“The article doesn't contain a direct quote.”

“These ideas include Hierarchical Temporal Memory (HTM) from 2004 and The Thousand Brains Theory of Intelligence from 2017.”

“MuseNet was not explicitly programmed with our understanding of music, but instead discovered patterns of harmony, rhythm, and style by learning to predict the next token in hundreds of thousands of MIDI files.”

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