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American politics is a battle between parties.
British politics is often a battle within parties.
Indian politics is both at the same time.
UK and India(infl by UK culture) both have this game of thrones atmosphere for top job - always on razors edge with various factions at play
🚨 NEW: A Labour source says Keir Starmer feels "betrayed"
"He gave everything to Labour, including sacrificing much of his children's teenage years to help make the party electable. He feels deeply betrayed, especially by those he believed were loyal to him"
Many people think any given ML project is 99% training.
In reality, it’s 50% evaluation, 40% data cleaning, 8% integration, and 2% training.
The first two set the noise floor for learning. No ML magic matters; the model cannot lower the noise floor, as that’s the optimal bound of Shannon encoding of your data.
Thus, not a single day goes by without me thinking about ontology. Even the old labels have to be constantly reviewed.
🚨 BREAKING: Keir Starmer is officially set to resign as Prime Minister
Several media reports say he'll outline a resignation timetable on Monday after consulting with his wife and family today
I thought this was a joke. Meta now has made 30-50% of software engineers on core teams become data labelers.
Their job is "giving human feedback on AI-generated Github repos" in an org called Agent Data Optimization.
Maybe we are all training data generators after all.
Last week, Argentina’s President Milei announced a new legal category for non-human corporations – companies run by #AI agents or robots. Like traditional corporations, they would be granted legal personhood. This could generate enormous new wealth, but very worryingly, it would also hand AIs an all-purpose key that grants access to our financial, economic and political systems. Full op-ed in today's @FT: https://t.co/w6DzOwByiq
Just learned:
Software engineers used to do manual data labeling at Scale AI while Alex Wang was CEO. After he left, new leadership joined, and were HORRIFIED to learn this. Stopped it ASAP
Now at Meta, software engineers are assigned manual data labeling... see the pattern?
We've raised $65 billion in Series H funding at a $965 billion post-money valuation, led by @AltimeterCap, Dragoneer, @Greenoaks, and @sequoia.
This investment will help us advance our research and expand our capacity to meet growing demand for Claude.
OpenAI and Anthropic are effectively telling the market they can't solve every problem with a generic AI coworker.
You don't pour billions into massive forward-deployed joint ventures if you think the next model release is going to take care of it.
In the cloud supercycle, semis led and software followed (and you didn't need Qualcomm or ARM to tell you the value was migrating up the stack).
In AI, the infra layer itself is telling us the application layer is a separate, massive opportunity they can't fully capture.
a16z's @joeschmidtiv on why the app layer isn't dead: https://t.co/84QN5Mj9T3
“A Google employee allegedly used confidential information to make more than $1.2 million through insider trading on a prediction market,�� said U.S. Attorney Jay Clayton. “Corporate insiders who misuse confidential information to trade for personal gain will be prosecuted.” @NewYorkFBI
https://t.co/v8GCUAO9Mk
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https://t.co/0f5d3ZWJ9W
A 19-year old broke into India's largest high school examination system of 2M+ students a year, the CBSE, and was able to view and CHANGE any students' marks.
He responsibly wrote to the team 3 months ago, and it took them 3 days to fix only one of the issues. Today, they took the entire website down.
This is a absolute embarrassment. The futures and lives of millions rests in the hands of the utterly incompetent. There is also no mass media reporting on the matter.
This topic is close to me because not only is this the education system I went through, but 12 years ago and silently for 5yrs since, I'd written about and reported a much less severe vulnerability allowing me to scrape these results too. More than a decade later, not much has changed.
This 19yo, Nisarga Adhikary, wrote a great piece outlining each vulnerability he reverse engineered:
- the master password leak
- the client-side 2fac / OTP validation workaround
- tokenless access to the entire internal app (dashboard, evaluator details, etc) setting dummy browser values
- changing any password without knowing the old one
- an IDOR vuln allowing you to act as any user and edit exam marks
For those interested in a beautiful study in security breaches, this is a must read (link below).
If there's any light at the end of the tunnel, it's that a 19yo who never went to college can do things 99% of top engineers couldn't figure out.
Uber COO and CEO got it backwards.
The highest leverage use of AI isn't "same headcount + more tokens = more cool features." It's using AI to let 25% HQ engineers deliver >=100% output, Eval the costs and ROI. If ur burning then top 25% is mid. Token costs are thru roof though.
Uber’s COO has said that it’s getting “harder to justify” its AI costs because there was no way to show a link between AI spend and any meaningful increase in useful features. This is the first time I’ve seen a company say this directly.
https://t.co/xUhZvtpwah