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The Data Dilemma: How 30 Trillion Tokens Taught Us That Bigger Isn’t Always Better The Night Ev...
https://medium.com/@malikzeeshan3.1417/the-data-dilemma-how-30-trillion-tokens-taught-us-that-bigger-isnt-always-better-08bcbca0647f?source=rss------machine_learning-5
#machine-learning #ai #generative-ai-tools #artificial-intelligence #llm
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#machine-learning #ai #generative-ai-tools #artificial-intelligence #llm
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Medium · The Data Dilemma: How 30 Trillion Tokens Taught Us That Bigger Isn’t Always Better
Diffusing Ghibli Maybe you’ve been hearing diffusion a lot since the new Chat GPT image release...
https://medium.com/@Joekbennett/diffusing-ghibli-0f5a6987fcf2?source=rss------machine_learning-5
#diffusion-models #ai #machine-learning
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#diffusion-models #ai #machine-learning
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Medium · Diffusing Ghibli - Joseph Bennett - Medium
Empowering Engineers with AI Background and motivation In the fast-paced world of software develo...
https://slack.engineering/empowering-engineers-with-ai/
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Engineering at Slack · Empowering Engineers with AI - Engineering at SlackBackground and motivation In the fast-paced world of software development, having the right tools can make all the difference. At Slack, we’ve been working on a set of AI-powered developer tools that are saving 10,000+ hours of developer time yearly, while meeting our strictest requirements for security, data protection, and compliance. In this post, we’ll…
New article on my website live!
Pythondeadlin.es Embraces AI: Now With 100% More Hallucinated Deadlines
Check it out here:
http://amplt.de/IcyDeficientBox
Bill Gates: "A.I. chatbots will teach kids to read within 18 months." (April 2023)
[R] Proof or Bluff? Evaluating LLMs on 2025 USA Math Olympiad
https://arxiv.org/abs/2503.21934v1
Discussions: https://discu.eu/q/https://arxiv.org/abs/2503.21934v1
arXiv.orgProof or Bluff? Evaluating LLMs on 2025 USA Math OlympiadRecent math benchmarks for large language models (LLMs) such as MathArena indicate that state-of-the-art reasoning models achieve impressive performance on mathematical competitions like AIME, with the leading model, o3-mini, achieving scores comparable to top human competitors. However, these benchmarks evaluate models solely based on final numerical answers, neglecting rigorous reasoning and proof generation which are essential for real-world mathematical tasks. To address this, we introduce the first comprehensive evaluation of full-solution reasoning for challenging mathematical problems. Using expert human annotators, we evaluated several state-of-the-art reasoning models on the six problems from the 2025 USAMO within hours of their release. Our results reveal that all tested models struggled significantly, achieving less than 5% on average. Through detailed analysis of reasoning traces, we identify the most common failure modes and find several unwanted artifacts arising from the optimization strategies employed during model training. Overall, our results suggest that current LLMs are inadequate for rigorous mathematical reasoning tasks, highlighting the need for substantial improvements in reasoning and proof generation capabilities.
HEADLINE: 'No Longer Think You Should Learn To Code,' Says CEO of AI Coding Startup
CORRECTED: CEO Of Company Whose Flimsy Business Model Is Only Hypothetically Viable If You Cant Code For Yourself; Says You Should Stop Learning To Code.
Supervised Learning in Artificial Neural Networks
Artificial Neural Networks are a fundamental component of machine learning, mimicking the human brain's structure and functioning. Within ANNs, one of the key paradigms is supervised learning, a powerful approach that enables the network to learn from labeled training data. In this article, we'll delve into the concept of supervised learning within artificial...
ml-nn.euSupervised Learning in Artificial Neural NetworksMachine Learning & Neural Networks Blog
Open source researchers at Princeton, Stanford, and Huawei are working on efficient neural theorem proving using neural networks.
https://arxiv.org/html/2502.07640v2
https://arxiv.org/html/2502.00212v4
https://arxiv.org/html/2501.18310v1
The benchmarks to follow
https://paperswithcode.com/sota/automated-theorem-proving-on-minif2f-test
https://trishullab.github.io/PutnamBench/leaderboard.html
arxiv.orgGoedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving
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Weee! is hiring Manager/Senior Manager of Machine Learning
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Job details https://jobsfordevelopers.com/jobs/manager-senior-manager-of-machine-learning-at-sayweee-com-feb-24-2025-fac2de?utm_source=mastodon.world&utm_medium=social&utm_campaign=posting
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jobsfordevelopers.comManager/Senior Manager of Machine Learning at Weee!Weee! is hiring Manager/Senior Manager of Machine Learning