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Thariq @trq212very weird thing happening rn technical people are sad, they think their skills are now useless non-technical people are desperately wishing they were more technical so they could use agents better
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Satya Mallick✓
@LearnOpenCV
CEO, https://t.co/CzUdJlxzJM. CEO, https://t.co/et3i4a7oGF Entrepreneur. Ph.D. ( Computer Vision & Machine Learning ). Author: https://t.co/olraDEG5Ue
828 Abonnements14.8K Abonnés4K Posts
very weird thing happening rn technical people are sad, they think their skills are now useless non-technical people are desperately wishing they were more technical so they could use agents better4824087.5K166K- Can Meta's Muse Wonder spot a goal? Our case study: 26/40 goal and shot clips matched the dataset, versus our teammate's 34/40. All 12 tool calls worked, but selected match clips included 2/5 goals. Pair it with a tracker and human review. Scope: Muse Wonder through OpenRouter, not Wonder Full. One venue, one full-match run, no audio. Not a benchmark. Footage: SoccerTrack v2 (atomscott/soccertrack-v2 on Hugging Face), CC BY 4.0. No endorsement by Meta, OpenRouter or the University of Tsukuba implied. #ComputerVision #OpenCV000173
- I was not sure if I wanted an iPhone Duo, but after experiencing it in real life for just 5 minutes, I’m 100% sure I don’t want it.
3092.1K - I have been running my computer vision and AI consulting company for 14 years and my investor, Mr. Mallick, has never asked send him a blurb.Sherwood @shcallawayI really dislike it when my investors ask me to "send a blurb". 1- You invested in my company. You should already know what I'm building. 2- You and I both know that generic blurbs never work. What works is a hand-crafted message from a warm contact (i.e. you, the investor). 3- On top of that, asking for a blurb is lazy. It throws the work back on me (the founder) at precisely the moment when I'm asking for support. If you REALLY wanted to be helpful, you would write the intro yourself + ask for my edits/approval. Just sayin'401652
I really dislike it when my investors ask me to "send a blurb". 1- You invested in my company. You should already know what I'm building. 2- You and I both know that generic blurbs never work. What works is a hand-crafted message from a warm contact (i.e. you, the investor). 3- On top of that, asking for a blurb is lazy. It throws the work back on me (the founder) at precisely the moment when I'm asking for support. If you REALLY wanted to be helpful, you would write the intro yourself + ask for my edits/approval. Just sayin'999334113K- You can use agents for turning in the assignments.Polymarket @PolymarketJUST IN: UC Berkeley math professor stops grading homework for correctness, saying widespread AI use has made it "pointless," and now awards credit simply for turning in assignments.100432
JUST IN: UC Berkeley math professor stops grading homework for correctness, saying widespread AI use has made it "pointless," and now awards credit simply for turning in assignments.3435567.7K461K- Same floor plan. Two 3D models. Which workflow was faster? We gave GPT-6.1 Terra and Claude Opus 5.5 the same dimensioned apartment drawing, then checked their exported meshes against the original CAD file that neither model saw. Both passed all 28 checks: 8 dimensions, 7 room connections and 13 openings. Neither needed a human fix. Small opening errors of 5–10 mm remained, within our preset 100 mm allowance. Terra's successful first run: 54.3 seconds. Opus's first run: 96.9 seconds. The catch: a 44-second Terra launch was blocked by our own tool-approval settings before it saw the drawing. Include it and Terra's initial total is 98.3 seconds, excluding setup-fix time. These are whole-agent workflow times, not pure model speed. One drawing and one run per model make this a case study, not a general ranking. Watch the full comparison: What would you count when comparing agent workflows: successful runs, or every attempt? Floor plan: Innerscene, "Three-bedroom apartment, 105 m²", CC0 1.0; rasterized from the source DXF. No endorsement by OpenAI, Anthropic or Innerscene implied. #AIAgents #ComputerVision #GPT61 #ClaudeAI
304449 - Nemotron 3.5 Super VL couldn't confirm step one. It still said "agrees." We showed NVIDIA's video model a robot assembling a lamp. It confirmed the bulb and shade, marked the base step as unobserved or uncertain, and wrote that the base never moved. Its verdict still agreed with the checklist. The robot actually completed all three steps. The verdict was right, but the model's own evidence did not support it. Then it counted 3 squats where our reference count is 2. Count them yourself. Ask for evidence. Check that the verdict follows from it. Then check the evidence against the video. Full test: Three case studies, not a benchmark. Reference answers were AI-assisted; human review is pending. Footage: FurnitureBench — Heo, Lee, Lee and Lim, CLVR Lab/KAIST (RSS 2023): Squats: "Squat - exercise demonstration video" by FitnessScape, CC BY 3.0, via Wikimedia Commons: License: — replay, half-speed playback, cropping and overlays added. Road-sign sample and model: NVIDIA. No endorsement implied. Cover is an illustration. #Nemotron #NVIDIA #ComputerVision #OpenCV000235
- I was talking to Prof. Ramamohan Paturi of UC San Diego yesterday and knew something massive was coming. Phew!Dan Roberts @danintheoryWe are announcing three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.2161.2K
We are announcing three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.3081.1K7.5K2.4M- Every automated check passed. The evidence box still missed the bus. We gave Roboflow Agent one minute of drone footage and asked whether an intersection was blocked. The workflow ran, the output parsed, and the structural checks passed—but the box offered as evidence for the blue bus did not contain it. Three checks for your next vision workflow: Does it run? Does it parse? Does the evidence support the answer? Watch the full tutorial: One feasibility test, not a benchmark or a measure of production accuracy. Footage: Songdo Traffic v2, Robert Fonod, Haechan Cho, Hwasoo Yeo and Nikolas Geroliminis. — CC BY 4.0: Resized and compressed; frames extracted and annotated. The dataset authors and Roboflow do not endorse this video. #ComputerVision #Roboflow #AIagents #OpenCV002424
- Same face, different conditions: 0.95 in the studio, 0.78 against a car-video frame. Day, camera and setting changed together—we cannot blame lighting alone. Enroll across days and cameras. Similarity is not accuracy. #OpenCV #ComputerVision Lighting data: Collin Gros (2019), Facial Recognition Dataset VIDEO (part 1 of 2), Mendeley Data V1. — CC BY 4.0 ( Used to derive scores and graphics; no dataset faces shown.000341
- Satya MallickRT @SahilBloom: I regret to inform you that nobody cares about your potential. Potential is nothing without execution. When you're young, everyone cares about your potential. You get used to focusing on it. But as you get older, no one cares about your potential. Just your delivery against it.02K050
- We tested Meta’s Muse Wonder on football—and checked what it actually saw. On 40 goal/shot clips, its best guess was correct on 26 (65%); our teammate got 34 (85%). A red marker hidden in one frame went unnoticed. Held for one second, it was spotted. Then we asked it to cut highlights from a 92-minute match. All 12 tool calls worked, but only 2 of the 5 goals landed in the selected clips. A useful coordinator needs reliable eyes. This is one controlled case study, not an overall benchmark. Watch on LearnOpenCV: “We Tested Meta's Muse Wonder on Football. It Missed Goals a Person Could See.” Data: SoccerTrack v2 (atomscott/soccertrack-v2, CC BY 4.0). #ComputerVision #MultimodalAI #ModelEvaluation #OpenCV
303520 - Nobody knowsRyan Petersen @typesfastWhat is the prevailing theory for why Fridays are such a popular work-from-home day?200526
What is the prevailing theory for why Fridays are such a popular work-from-home day?25161K546K- The astonishing rise of China and the decline of Europe has been a work in progress for years. Yet, it’s unbelievable when you experience it first hand.DHH @dhhI've been blown away by the energy, optimism, and hard work that has created the China I've seen on this trip. It had been seven years since I was last here, and it might as well have been forty. Invigorating to see what's possible. The West has no excuse for its managed decline.101591
I've been blown away by the energy, optimism, and hard work that has created the China I've seen on this trip. It had been seven years since I was last here, and it might as well have been forty. Invigorating to see what's possible. The West has no excuse for its managed decline.2583136.8K468K- Datalab’s Indra OCR runs on CPUs, with no GPU. Its recognizer has about one million parameters. Datalab reports 49 pages/sec on a 32-core server; on 4 cores, about 7 pages/sec. Hardware matters when reading benchmark headlines. In our upside-down scan demo, it rotated the page, detected lines, determined reading order and wrote Markdown in 344 ms on 2 vCPUs. Built for clean printed documents; handwriting, faded scans and complex tables remain limitations. What document type should we test against Tesseract and PaddleOCR next? Sources: Demo page: Attention Is All You Need — Vaswani et al. (2017). #OCR #ComputerVision #DocumentAI #OpenCV #Python306436
- Would I let a video model sign off on completed work? Only after checking how it reached the verdict. Our Nemotron 3.5 Super VL test is a useful example: the robot completed the checklist, but the model could not support one step and still agreed. A correct verdict alone would hide that failure. We also tested a road sign and squat counting. Three case studies—not a benchmark. Human review of references is pending. Full video, “Nemotron 3.5 Super VL Tested: A Correct Answer for the Wrong Reason,” on LearnOpenCV: Video sources: NVIDIA; FurnitureBench (CLVR Lab/KAIST); FitnessScape (CC BY 3.0). Full credits in the description. Thumbnail is an illustration. What would you check beyond the final answer? #AI #ComputerVision
004456 - I finally watched the movie. The staring is nothing compared to the head-nod that messes your brain.Satya Mallick @LearnOpenCVWhen the blink detector has more independent validation than Theranos. 😅 Built with HRFFA: per-person blink counting, facial landmarks, and synchronized audio/visual markers.003783
- When the blink detector has more independent validation than Theranos. 😅 Built with HRFFA: per-person blink counting, facial landmarks, and synchronized audio/visual markers.751072.7K589K
