Sadiq Ali spreading anti-India propaganda online: Read how the Canada-based Pakistani is using fake content to ‘create so much anti-India hatred that it becomes normal to kill Indians’
https://t.co/xABOl99O4P
As expected, it was all part of the Pakistani hate and propaganda wing, DGISPR. Look at how they're boasting about hacking the algorithm and requesting their followers to normalize hate against Indians to the point where people don't even hesitate to kill them.
India trains the engineer.
America files the patents.
Gurtej Sandhu was raised in Amritsar and trained at IIT Delhi.
He now holds 1,299 US patents at Micron, Edison topped out at 1,093.
Sandhu is the 7th most prolific inventor in American history.
His titanium nitride deposition work is why every DRAM cell in your phone and every GPU training a foundation model actually holds charge.
Micron, Samsung, and SK Hynix own 95% of global DRAM.
None of them are Indian.
We export the inventor.
We import the chip.
Software horror: litellm PyPI supply chain attack.
Simple `pip install litellm` was enough to exfiltrate SSH keys, AWS/GCP/Azure creds, Kubernetes configs, git credentials, env vars (all your API keys), shell history, crypto wallets, SSL private keys, CI/CD secrets, database passwords.
LiteLLM itself has 97 million downloads per month which is already terrible, but much worse, the contagion spreads to any project that depends on litellm. For example, if you did `pip install dspy` (which depended on litellm>=1.64.0), you'd also be pwnd. Same for any other large project that depended on litellm.
Afaict the poisoned version was up for only less than ~1 hour. The attack had a bug which led to its discovery - Callum McMahon was using an MCP plugin inside Cursor that pulled in litellm as a transitive dependency. When litellm 1.82.8 installed, their machine ran out of RAM and crashed. So if the attacker didn't vibe code this attack it could have been undetected for many days or weeks.
Supply chain attacks like this are basically the scariest thing imaginable in modern software. Every time you install any depedency you could be pulling in a poisoned package anywhere deep inside its entire depedency tree. This is especially risky with large projects that might have lots and lots of dependencies. The credentials that do get stolen in each attack can then be used to take over more accounts and compromise more packages.
Classical software engineering would have you believe that dependencies are good (we're building pyramids from bricks), but imo this has to be re-evaluated, and it's why I've been so growingly averse to them, preferring to use LLMs to "yoink" functionality when it's simple enough and possible.
We are thrilled to announce that Google’s Satellite Embedding dataset, powered by @GoogleDeepMind's AlphaEarth Foundations model, has been updated for 2025. This additional year of coverage now unlocks the ability to look back, compare, and detect change across the planet with unprecedented clarity. Learn more here ➡️ https://t.co/yCHMhXCnq6
Part of Google's Earth AI, the new data represents the state of the planet throughout 2025, distilling petabytes of multi-sensor data into a 64-dimensional embedding for every 10 meter pixel.
What’s new in this update? 🧵👇
- 🌍 2025 Data: The state of the planet throughout 2025 is now available on the Earth Engine Data Catalog and Google Cloud Storage.
- 🔬 Unprecedented Change Detection: Because these embeddings capture subtle spectral, spatial and temporal signatures, they make it easy to spot significant year-over-year changes without the heavy lifting of raw image processing.
- 💚 Long-term Commitment: We are formalizing our commitment to the ongoing production of these annual layers to support your operational workflows.
Since we first launched the Satellite Embedding dataset, we’ve been inspired by how our community is putting this data to work. Applications are ranging from ecosystem mapping and agricultural crop-typing to carbon stock prediction. We can’t wait to see what you do next.
#EarthEngine #GeoAI #DeepMind
We are thrilled to announce that Google’s Satellite Embedding dataset, powered by @GoogleDeepMind's AlphaEarth Foundations model, has been updated for 2025. This additional year of coverage now unlocks the ability to look back, compare, and detect change across the planet with unprecedented clarity. Learn more here ➡️ https://t.co/yCHMhXCnq6
Part of Google's Earth AI, the new data represents the state of the planet throughout 2025, distilling petabytes of multi-sensor data into a 64-dimensional embedding for every 10 meter pixel.
What’s new in this update? 🧵👇
- 🌍 2025 Data: The state of the planet throughout 2025 is now available on the Earth Engine Data Catalog and Google Cloud Storage.
- 🔬 Unprecedented Change Detection: Because these embeddings capture subtle spectral, spatial and temporal signatures, they make it easy to spot significant year-over-year changes without the heavy lifting of raw image processing.
- 💚 Long-term Commitment: We are formalizing our commitment to the ongoing production of these annual layers to support your operational workflows.
Since we first launched the Satellite Embedding dataset, we’ve been inspired by how our community is putting this data to work. Applications are ranging from ecosystem mapping and agricultural crop-typing to carbon stock prediction. We can’t wait to see what you do next.
#EarthEngine #GeoAI #DeepMind
@Chansoo@grok extrapolate that the chart above to demonstrate the theoretical vs observed AI capability for the transportation vertical, considering Tesla FSD’s impact on the miles already driven autonomously in North America
i regret to inform you that personal growth rarely comes from acquiring new knowledge and always from periods of intense humility (i.e. your ego finally relenting)
The brutal beheading of a hardworking Indian American immigrant in front of his wife & son is horrific. The murderer had multiple prior arrests for violent theft & child endangerment & was undocumented. He should not have been free on American streets. https://t.co/7LDNITCd9Y
anyone buying a Macbook is probably creating positive value (highly correlated)
and that value would show up elsewhere eg a job (more income tax) / revenue (more tax/jobs) / research etc
so not taxing Macbooks at a high rate may yield a net positive…