The Hidden Price of Training ML Models 𝑇ℎ𝑖𝑠 𝑝𝑜𝑠𝑡 𝑖𝑠 𝑝𝑎𝑟𝑡 𝑜𝑓 𝑡ℎ𝑒 𝑠𝑒𝑟𝑖𝑒𝑠 𝑀𝐿𝑂𝑝𝑠 𝑖𝑛 𝑡ℎ𝑒 𝑤𝑖𝑙𝑑 𝑎𝑛𝑑 𝑏𝑎𝑠𝑒𝑑 𝑜𝑛 𝑡ℎ𝑒 𝑝𝑎𝑝𝑒𝑟 “𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒𝑠 𝑖𝑛 𝐷𝑒𝑝𝑙𝑜𝑦𝑖𝑛𝑔 𝑀𝑎𝑐ℎ𝑖𝑛𝑒 𝐿𝑒𝑎𝑟𝑛𝑖𝑛𝑔: 𝑎 𝑆𝑢𝑟𝑣𝑒𝑦 𝑜𝑓 𝐶𝑎𝑠𝑒

📢 𝗜𝘀𝘀𝘂𝗲 𝟲𝟰𝟯 𝗶𝘀 𝗢𝘂𝘁! In today's edition, you can find: 📰 𝗡𝗲𝘄𝘀: - Robot lawnmower designed to also pick fruit and throw your dog a ball - OpenAI links up with Broadcom to produce its own AI chips - Why is an Amazon-backed AI startup making Orson Welles fan

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Why Simple Models Win in Production 𝑇ℎ𝑖𝑠 𝑝𝑜𝑠𝑡 𝑖𝑠 𝑝𝑎𝑟𝑡 𝑜𝑓 𝑡ℎ𝑒 𝑠𝑒𝑟𝑖𝑒𝑠 𝑀𝐿𝑂𝑝𝑠 𝑖𝑛 𝑡ℎ𝑒 𝑤𝑖𝑙𝑑 𝑎𝑛𝑑 𝑏𝑎𝑠𝑒𝑑 𝑜𝑛 𝑡ℎ𝑒 𝑝𝑎𝑝𝑒𝑟 “𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒𝑠 𝑖𝑛 𝐷𝑒𝑝𝑙𝑜𝑦𝑖𝑛𝑔 𝑀𝑎𝑐ℎ𝑖𝑛𝑒 𝐿𝑒𝑎𝑟𝑛𝑖𝑛𝑔: 𝑎 𝑆𝑢𝑟𝑣𝑒𝑦 𝑜𝑓 𝐶𝑎𝑠𝑒

📢 𝗜𝘀𝘀𝘂𝗲 𝟲𝟰𝟮 𝗶𝘀 𝗢𝘂𝘁! In today's edition, you can find: 📰 𝗡𝗲𝘄𝘀: - Orchard Robotics raises $22M for farm vision AI - Why AI gets stuck in infinite loops – but conscious minds don't - Switzerland releases its own AI model trained on public data ... and more!

#FridayHumor

The Labeling Bottleneck 𝑇ℎ𝑖𝑠 𝑝𝑜𝑠𝑡 𝑖𝑠 𝑝𝑎𝑟𝑡 𝑜𝑓 𝑡ℎ𝑒 𝑠𝑒𝑟𝑖𝑒𝑠 𝑀𝐿𝑂𝑝𝑠 𝑖𝑛 𝑡ℎ𝑒 𝑤𝑖𝑙𝑑 𝑎𝑛𝑑 𝑏𝑎𝑠𝑒𝑑 𝑜𝑛 𝑡ℎ𝑒 𝑝𝑎𝑝𝑒𝑟 “𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒𝑠 𝑖𝑛 𝐷𝑒𝑝𝑙𝑜𝑦𝑖𝑛𝑔 𝑀𝑎𝑐ℎ𝑖𝑛𝑒 𝐿𝑒𝑎𝑟𝑛𝑖𝑛𝑔: 𝑎 𝑆𝑢𝑟𝑣𝑒𝑦 𝑜𝑓 𝐶𝑎𝑠𝑒 𝑆𝑡𝑢𝑑𝑖𝑒𝑠”

📢 𝗜𝘀𝘀𝘂𝗲 𝟲𝟰𝟭 𝗶𝘀 𝗢𝘂𝘁! In today's edition, you can find: 📰 𝗡𝗲𝘄𝘀: - OTC nasal spray seemed to cut Covid infections by 67% in mid-sized trial - OpenAI acquires product testing startup Statsig and shakes up leadership team - Tech that could turn Zigbee light

Data Cleaning and Integration 𝑃𝑎𝑟𝑡 𝑜𝑓 𝑡ℎ𝑒 𝑠𝑒𝑟𝑖𝑒𝑠 “𝑀𝐿𝑂𝑝𝑠 𝑖𝑛 𝑡ℎ𝑒 𝑤𝑖𝑙𝑑” 𝑏𝑎𝑠𝑒𝑑 𝑜𝑛 𝑡ℎ𝑒 𝑝𝑎𝑝𝑒𝑟 𝐶ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒𝑠 𝑖𝑛 𝐷𝑒𝑝𝑙𝑜𝑦𝑖𝑛𝑔 𝑀𝑎𝑐ℎ𝑖𝑛𝑒 𝐿𝑒𝑎𝑟𝑛𝑖𝑛𝑔: 𝑎 𝑆𝑢𝑟𝑣𝑒𝑦 𝑜𝑓 𝐶𝑎𝑠𝑒 𝑆𝑡𝑢𝑑𝑖𝑒𝑠 𝑏𝑦 𝐴𝑛𝑑𝑟𝑒𝑖

📢 𝗜𝘀𝘀𝘂𝗲 𝟲𝟰𝟬 𝗶𝘀 𝗢𝘂𝘁! In today's edition, you can find: 📰 𝗡𝗲𝘄𝘀: - OpenAI acquires Statsig - Is AI the end of software engineering or the next step in its evolution? - WhatsApp fixes 'zero-click' bug used to hack Apple users with spyware ... and more! 💡📚

Training the model isn’t the hardest part. Finding the right data is When people talk about machine learning, they usually imagine massive neural nets, GPUs, and fancy algorithms. But here’s the truth from real-world deployments: most projects stall before training even begins.

📢 𝗜𝘀𝘀𝘂𝗲 𝟲𝟯𝟵 𝗶𝘀 𝗢𝘂𝘁! In today's edition, you can find: 📰 𝗡𝗲𝘄𝘀: - Norway eyes 200-250 MW floating nuclear reactors to power industry - Science research gets more engagement on Bluesky than X, study finds - Research roundup: "jelly ice," regenerating snail

Github: claude-subagents https://t.co/32NDYy5sNa

Machine Learning’s biggest challenge isn’t building models — it’s deploying them We’ve all seen the hype around AI models. But ask anyone who’s actually put ML into production, and you’ll hear a different story: 👉 Models don’t fail because they’re inaccurate. 👉 They fail

📢 𝗜𝘀𝘀𝘂𝗲 𝟲𝟯𝟴 𝗶𝘀 𝗢𝘂𝘁! In today's edition, you can find: 📰 𝗡𝗲𝘄𝘀: - Chatbots can be manipulated through flattery and peer pressure - GenAI to automate federal worker tasks predicted to cut 300k jobs by end of year - First AI Psychosis Case Ends in

#FridayHumor

12/12 Transformer beyond translation 𝑇ℎ𝑖𝑠 𝑝𝑜𝑠𝑡 𝑖𝑠 𝑎 𝑝𝑎𝑟𝑡 𝑜𝑓 𝑎 𝑠ℎ𝑜𝑟𝑡 𝑠𝑒𝑟𝑖𝑒𝑠 𝑎𝑏𝑜𝑢𝑡 𝑡ℎ𝑒 𝑟𝑒𝑠𝑒𝑎𝑟𝑐ℎ 𝑝𝑎𝑝𝑒𝑟 “𝐴𝑡𝑡𝑒𝑛𝑡𝑖𝑜𝑛 𝐼𝑠 𝐴𝑙𝑙 𝑌𝑜𝑢 𝑁𝑒𝑒𝑑” (2017) 𝑤ℎ𝑖𝑐ℎ 𝑖𝑛𝑡𝑟𝑜𝑑𝑢𝑐𝑒𝑑 𝑡ℎ𝑒 𝑇𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑒𝑟 – 𝑡ℎ𝑒

📢 𝗜𝘀𝘀𝘂𝗲 𝟲𝟯𝟳 𝗶𝘀 𝗢𝘂𝘁! In today's edition, you can find: 📰 𝗡𝗲𝘄𝘀: - Unpacking Passkeys Pwned: Possibly the most specious research in decades - The personhood trap: How AI fakes human personality - Seeing infrared: contact lenses that grant 'super-vision' ...

11/12 Why self-attention is fast (and smart) 𝑇ℎ𝑖𝑠 𝑝𝑜𝑠𝑡 𝑖𝑠 𝑎 𝑝𝑎𝑟𝑡 𝑜𝑓 𝑎 𝑠ℎ𝑜𝑟𝑡 𝑠𝑒𝑟𝑖𝑒𝑠 𝑎𝑏𝑜𝑢𝑡 𝑡ℎ𝑒 𝑟𝑒𝑠𝑒𝑎𝑟𝑐ℎ 𝑝𝑎𝑝𝑒𝑟 “𝐴𝑡𝑡𝑒𝑛𝑡𝑖𝑜𝑛 𝐼𝑠 𝐴𝑙𝑙 𝑌𝑜𝑢 𝑁𝑒𝑒𝑑” (2017) 𝑤ℎ𝑖𝑐ℎ 𝑖𝑛𝑡𝑟𝑜𝑑𝑢𝑐𝑒𝑑 𝑡ℎ𝑒 𝑇𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑒𝑟 –

📢 𝗜𝘀𝘀𝘂𝗲 𝟲𝟯𝟲 𝗶𝘀 𝗢𝘂𝘁! In today's edition, you can find: 📰 𝗡𝗲𝘄𝘀: - Verily is closing its medical device program, shifts resources to AI - Bluesky now platform of choice for science community - With Starship, SpaceX encounters an obstacle that haunted NASA's

Github: langextract https://t.co/CTjuzwOI1k