Kaushik Bhatta (KB)

Jensen is one the smartest and most far seeing folks the world. "If an AI scientist warns people that AI is going to permeate across radiology and radiologists are going to get wiped out, it might seem helpful but it's hurtful. If we convince everybody not to be radiologists and we now need radiologists, that actually is hurtful to society. "It is hurtful to convince all the young college graduates not to study software engineering because we are going to need more software engineers than ever. That's hurtful." "Scaring people with nonsensical things, which are not going to happen, that this is an existential threat, there's a 20% chance that is is existential, that's ridiculous. "That it's going to wipe out 50% of college level jobs. "That is it going to completely destroy democracy. "These kinds of comments are not helpful. They are made by...CEOS. And you become a CEO, maybe you adopt a God complex and somehow you know everything." Brutal. And right.

Veteran buried his eldest and it’s not looking good for his two others. Posting for any connections, help that can be made while they fight for time.

It’s time to expose a huge scam in AI startups: Contracted ARR The reason many AI startups are crushing revenue records is because they are using a dishonest metric The biggest funds in the world are supporting this and misleading journalists for PR coverage. The setup: Company signs 3-year enterprise deals. Year 1 is discounted (say $1M), Year 2 steps up ($2M), Year 3 is full price ($3M). They report $3M as “ARR” — even though they’re only collecting $1M right now. The worst part: The customer has an opt-out option at 12 months! It’s not actually a 3 year contract. In the chart below, by Q5 the company is trumpeting ~$100M “ARR” to press, while actual cash-generating, in-effect ARR is ~$35M. That’s ~3x inflation. On top of this, enterprise AI companies are bundling full-time “forward deployed engineers” into deals massively reducing margins, sometimes producing Year 1 negative margins. At some point customers are going to start triggering their opt-out clauses or aggressively negotiating down Year 3 pricing. And a wave of enterprise AI companies may collapse.

India is the world's largest producer of mangos, growing roughly 45-50% of the world's mangos every year. However, less than 1% of those mangos get exported due to the fact that people in India eat almost all of them.

Artemis II, we’re ready for ya! 🌎 NASA’s Earth science missions provide observations used to forecast wind, turbulence, and temperature. Those forecasts come from the Goddard Earth Observing System, or GEOS, which helps teams prepare for a safe splashdown.

🚨Google built an invisible watermark into every image Gemini has ever generated. Over 10 billion pieces of content marked. One unemployed engineer just cracked it open. With 200 black images and math. It's called reverse-SynthID. SynthID is Google DeepMind's invisible watermark. It's embedded at the pixel level into every image, video, audio, and text generated by Gemini. Invisible to the human eye. Designed to survive cropping, compression, screenshots, and format changes. It was supposed to be unbreakable. Here's how he broke it: → Generated 200 pure black and pure white images from Gemini → When you average enough pure-black AI images, every non-zero pixel IS the watermark. Nothing to hide behind. Just the signal, naked. → Used FFT spectral analysis to map the exact carrier frequencies → Discovered the watermark uses a fixed phase template — identical across every image from the same model → Cross-image phase coherence at carrier frequencies: over 99.5% → Built a detector that identifies SynthID watermarks with 90% accuracy → Built a V3 bypass that drops 91% of the phase coherence and 75% of carrier energy — at 43+ dB PSNR. Almost zero visible quality loss. No neural networks. No proprietary access. No leaked code. Just signal processing and too much free time. Here's the wildest part: The green channel carries the strongest watermark signal. The carrier frequencies change based on image resolution. And the entire phase template is fixed — meaning every single Gemini image carries the same fingerprint structure. One engineer. 200 black images. A Fourier transform. That's all it took to reverse-engineer a system protecting 10 billion+ pieces of content. 519 GitHub stars. 39 forks. Python. Research and educational purposes only. 100% Open Source. (Link in the comments)

Lots of love for Gemma 4! Team just told me it’s already had 10M+ downloads since last week’s launch. Gemma models have now been downloaded 500M+ times! Excited to see what you all are creating 👀

Claude Mythos is Delusional