Wow exciting stuff! 😀 Have you tried it with long-form coding tasks?
GENERATIVE AI
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Vibe Coding vs Thoughtful Coding with AI: Key Differences
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*in my mind, vibe coders are just yolo’ing code with AI – which i think of distinctly from “coding with AI” which is more thoughtful
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Democratizing AI Capability for Individuals and Small Groups
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And now we're trying to make it so very small groups, or even individuals, can harness this capability. The journey continues! 😀
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AI in Medicine and Domain-Specific Applications with fastai
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Showing that this could be applied to transform an important domain (
@enlitic doing AI in medicine) was the next big step. Then enabled others to do it in their own domains (with @fastdotai
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30 Years of AI Research Continues Through Answer.ai
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I've been working for the last 30 years on a single theme really, with various windings diversions along the way. But it hasn't changed too much, and I think we now have a vehicle (
@answerdotai
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Veo 3 Video Generation: Fast Results with Simple Prompts
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Most of these were on the faster, cheaper Veo 3, using a dumb prompt, and worked the first time. For Ophelia, I just used the famous painting itself and the prompt: she sits up and says "Actually, I think I am over Hamlet"
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Upstage Launches Solar-Pro2 Frontier Model with Advanced Reasoning
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Finally, @upstageai is proud to announce the launch of its #Frontier model #SolarPro2. We sincerely thank everyone who used our solar-pro2-preview and provided valuable feedback. Leveraging your input, we have incorporated newly developed learning methodologies, enhanced data curation techniques for improved data quality, general reasoning data synthesis methods, and verifiable reward technologies to create this advanced model. The Solar-Pro2 model demonstrates exceptional performance on high-difficulty reasoning benchmarks, including MMLU-Pro, Math500, AIME, and SWE-Bench. Moreover, it excels in Arena-Hard-Auto, a rigorous evaluation framework adapted from LMSYS’s LLMArena, which focuses exclusively on extremely challenging problems. Arena-Hard-Auto is not a simple multiple-choice test—it evaluates answers against those generated by top-tier models, akin to lengthy essay or subjective exams. This benchmark is so demanding that non-Frontier models often score only 10–20%, making it nearly impossible to publish results. Solar-Pro2 (reasoning) achieves a 46% score on Arena-Hard-Auto and 71% on Ko-Arena-Hard-v0.1, surpassing even the highest-quality Korean answers. Solar-Pro2 is now available for immediate use at chat.upstage.ai/ and via API (model name: solapr-pro2). To encourage broader adoption, we offer a TRY-SOLAR-PRO2 $50 credit code (valid until August 31).
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Expert Data Powers Next Wave of GenAI
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From the @RaiseSummit Paris stage @ajratner made one thing clear: Expert data powers the next wave of GenAI. #SnorkelAI #GenAI #AIInfrastructure
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100M Parameter Networks Matching O3 Pro in 100 Years?
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in 100 years, will we have 100M parameter neural networks that perform at the level of today's o3 pro?
— dr. jack morris (@jxmnop) 9 juillet 2025
and if so, how? https://t.co/i80ZeIH3Kyin 100 years, will we have 100M parameter neural networks that perform at the level of today's o3 pro? and if so, how?
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Compressing Knowledge: Can Small LLMs Match o3 Pro Capability?
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more on this idea in our pod with @jxmnop
— swyx 🐣 (@swyx) 9 juillet 2025
but his favorite part is highlighted here: the "cognitive core" question of how smol we can compress knowledge and LLMs so that they have o3 pro level capability with only x00m parameters?https://t.co/4Skn4AKlgu pic.twitter.com/dFhlToWKC9more on this idea in our pod with @jxmnop but his favorite part is highlighted here: the "cognitive core" question of how smol we can compress knowledge and LLMs so that they have o3 pro level capability with only x00m parameters?