AlphaSignal

Finally found a way to explain what we do in a single image.

Amazing. You can now convert images of equations into LaTeX code with simple Python library. Use the command line tool by calling pix2tex: 𝐩𝐢𝐩 𝐢𝐧𝐬𝐭𝐚𝐥𝐥 "𝐩𝐢𝐱𝟐𝐭𝐞𝐱[𝐠𝐮𝐢]" 𝐟𝐫𝐨𝐦 𝐏𝐈𝐋 𝐢𝐦𝐩𝐨𝐫𝐭 𝐈𝐦𝐚𝐠𝐞 𝐟𝐫𝐨𝐦 𝐩𝐢𝐱𝟐𝐭𝐞𝐱.𝐜𝐥𝐢 𝐢𝐦𝐩𝐨𝐫𝐭 𝐋𝐚𝐭𝐞𝐱𝐎𝐂𝐑 𝐢𝐦𝐠 = 𝐈𝐦𝐚𝐠𝐞.𝐨𝐩𝐞𝐧('𝐩𝐚𝐭𝐡/𝐭𝐨/𝐢𝐦𝐚𝐠𝐞.𝐩𝐧𝐠') 𝐦𝐨𝐝𝐞𝐥 = 𝐋𝐚𝐭𝐞𝐱𝐎𝐂𝐑() 𝐩𝐫𝐢𝐧𝐭(𝐦𝐨𝐝𝐞𝐥(𝐢𝐦𝐠)) Repo: https://lnkd.in/d8eTH-iq #AI #ChatGPT#DataScience #ML

Wow. Amazon just released Q-Developer, a powerful GenAI assistant for software development that is also an expert in AWS. You can write queries in natural language, get real-time help with data pipelines, and even design ML models. It integrates directly into your IDE, Key features: ▸ 80% faster development tasks (internal study) ▸ 40% increase in developer productivity ▸ Optimized for AWS operations and cloud cost efficiency ▸ Autonomous agents for software upgrades and transformations You can learn how to use it via the AWS Developer Center: https://fnf.dev/4hyXQmx *This post is in collaboration with AWS Developers.

This is next-level engineering. Elon Musk explains how xAI built a massive GPU cluster from an abandoned factory. They had to solve power fluctuations, cooling, and networking, to keep 200,000 GPUs running smoothly. Real-world engineering is about solving unexpected problems while racing against time, and this is a practical example. ↓ Are you an AI developer? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.

A new enterprise model called Jamba 1.6 is now outperforming models like Mistral in quality, speed, and long context. It might be the best model for private deployment: 1. 𝗜𝘁’𝘀 𝗼𝗽𝗲𝗻 – No data leakage, available for on-prem or in-VPC deployments. 2. 𝗜𝘁 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘀 𝘁𝗼𝗽 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 – Proven by Arena Hard, RAG, and Long Context QA benchmarks. 3. 𝗜𝘁 𝘀𝘂𝗿𝗽𝗮𝘀𝘀𝗲𝘀 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗼𝗿𝘀 𝗼𝗻 𝘀𝗽𝗲𝗲𝗱 – Faster than Mistral, Llama, and Cohere in enterprise workloads. Key Features: ✅ Available in large & mini versions for different enterprise needs. ✅ Outperforms open competitors in quality/speed. ✅ Excels on Long Context Tasks – 256K context window. ✅ Mamba-Transformer MoE design for cost and efficiency gains. ✅ Deployable Anywhere – Self-hosted or AI21 SaaS for full data security control. Try it here: https://lnkd.in/ew9pfrmG

If AI has memorized the entire corpus of human knowledge, why hasn't it made the next major discovery? Humans with far more limited information achieve breakthroughs all the time. Is this a fundamental limitation of large language models? ↓ Are you an AI developer? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.

OpenAI o3-mini scores above 120 IQ. This is PhD-level intelligence only a few clicks away. How much higher will o3-mini-high raise the bar? ↓ Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.

You can add Generative AI to Pandas and chat with your dataset with a single line of code. The PandasAI library allows you to analyze complex data frames, plot visualizations, and generate report just by using natural language. Repo in comments. ♻️ Repost this if you found it useful. ↓ Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.

Impressive. You can now run open-source models 10x faster like DeepSeek-R1 (671b) using SambaNova Systems. By using RDUs instead of GPUs, their platform runs models faster through massive in-memory storage, efficient dataflow design, and instant model switching. It lets you: ▸ Run DeepSeek-R1 (671b) instantly—no setup, no infra headaches. ▸ Faster inference than GPUs—optimized for high-throughput workloads. ▸ Hold hundreds of models in memory—no reloading, no slowdowns. ▸ Switch models in microseconds—ideal for multi-model workflows. ▸ Train and fine-tune on the same platform. Try it here, it's free: https://fnf.dev/4igJ6Zt

ChatGPT can now use Claude. Imagine being able to mix the outputs and create the ultimate LLM. ↓ Are you an AI developer? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.