Siddharth M

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Siddharth M

Siddharth M

@sgm_force

Assistant Prof (Information Systems), PhD in Information Systems. Lover of movies, history, music, politics, cricket and chess.

India 가입일 Aralık 2015
43 팔로잉49 팔로워
Siddharth M 리트윗함
Ramesh Srivats
Ramesh Srivats@rameshsrivats·
Now that Vijay has got the support of 118 MLAs, the Governor is going to send him back to do KYC, get copies of their Aadhaar cards and PAN cards, and get a small video from each confirming their consent (file size < 5MB).
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The Serfs (youtube.com/theserftimes)
The Met Gala was annoying when the world wasn't on fire. Now it just seems like a deranged spectacle by rich deluded sociopaths
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Daniel Jeffries
Daniel Jeffries@Dan_Jeffries1·
The number of jobs in the future is endless because the problems to solve are endless. Jobs multiply as we get more complex. No AI or human can solve all problems and all the work to do in the Universe because those problems are limitless. The problems are endless and infinite. Technology and automation are nothing but abstractions. The old way gets automated and we move up the stack to solve more problems. We used to live in mud huts. Hammers and nails and boards automated parts of the old problem of "build a place to live." Once solved we got more complex houses and buildings that brought their own problems as they brought more complexity, so we got new jobs like stone mason and architect and more. Complexity breeds new problems and new solutions and new jobs. When we got steel and concrete we got skyscrapers. Each problem solved is an abstracted solution for a previous problem that stacks on top of other abstractions. That's all that automation and technology is at the deepest levels. The jobs are endless because the problems to solve are endless. Understand this and you understand the future. Misunderstand it and your error compounds and radiates out, corrupting your understanding.
Rohan Paul@rohanpaul_ai

Brilliant explanation from Nvidia CEO Jensen Huang on AI's job effect: In software, AI makes coding faster, but that does not mean fewer engineers are needed. Before AI, we could write 1 billion lines of code; now, with AI, we can aim for 1 trillion.

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Backpacking Daku
Backpacking Daku@outofofficedaku·
Pan Shop in Czech Republic can be named Pan Prague
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Cinema Tweets
Cinema Tweets@CinemaTweets1·
Man on Fire has been turned into a TV series on Netflix. I’m not here to disparage something I haven’t see, but I have one question: why? Just…why? Why touch Denzel & Tony? You think you can play The Beatles better than The Beatles? Please can we get more new stories around here
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Reid Southen
Reid Southen@Rahll·
More money for worse work that you have to fix, good stuff this AI thing, thanks Nvidia.
Reid Southen tweet media
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🌻
🌻@naanbiological·
Commercial Cylinder ₹1000 मंहगा नहीं हुआ है, ₹993 हुआ है।
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The New Yorker
The New Yorker@NewYorker·
A 2025 study out of M.I.T. cautioned that “the integration of LLMs into learning environments may inadvertently contribute to cognitive atrophy.” This danger hasn’t slowed the advancement of A.I. in schools. newyorker.com/culture/progre…
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James Pethokoukis ⏩️⤴️
James Pethokoukis ⏩️⤴️@JimPethokoukis·
"A decade ago, AI was supposed to replace radiologists. Today, radiologists make more than $500,000 per year, and their employment continues to grow, see chart below. Reading scans is a task, not a job, and when the task gets cheaper, demand for the job grows."
James Pethokoukis ⏩️⤴️ tweet media
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Tarun Gautam
Tarun Gautam@TARUNspeakss·
Swati Maliwal has officially joined BJP today. Can’t wait her to see campaigning for Brijbhushan Singh in UP and against female wrestlers in Haryana.
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macintog
macintog@macintogdev·
One of my first jobs was data entry at a car auction broker. A dozen people were entering condition reports & sales data for nationwide car resale. I'd been doing some Access 2.0 work on a copy of production for fun. One day, the whole network suddenly felt very slow and buggy. So I made a local backup of the database, just in case. Twenty minutes later. The network went down. Everything. An hour later, our director walked in with someone I'd never seen in tow. He was slumped over, sheet-white, and looked like he was five minutes on either side of vomiting. Our director announced that: - the database and all of our work had been wiped out - the backups had been broken for several weeks - we were going to be spending the next few weeks just trying to piece together thousands of hours of work we had already done once. I raised my hand and said I'd made a backup an hour ago, and asked where they would like me to upload it. They both stared at me (along with everyone else) like I had sprouted tentacles. Twenty minutes later we were back to work. No one ever said another word about it. No questions. No bonus. No thank you. This was a very worthwhile life lesson that has paid 100x dividends.
Polymarket@Polymarket

NEW: Claude-powered coding agent reportedly deleted a company’s production database, and backups, in 9 seconds.

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Aaron Levie
Aaron Levie@levie·
Noticing an interesting version of gell-man amnesia where people use AI for their job and see all the various things they have to do in the “last mile”, but then look at someone else’s job and think that AI will eliminate it immediately. We all have a much deeper appreciation for the nuances and complexities of the work that we do every day. We run into issues about accessing data, we know how much context is needed to get AI models to work the way we need, we have to review the output of the AI to make sure it’s accurate, and then we have to incorporate that work into some broader business process. We see all those steps deeply for the work that we do. Then, a moment later, we see AI do something in a foreign space and think that it can go automate that entire function. We tend to dramatically underestimate the work that goes into making the AI work just as effectively in those jobs. This is reason to be skeptical about many of the theories of job loss. It’s coming from the lens of being able to automate individual tasks with AI, without understanding all the work that goes into doing the job fully.
Karri Saarinen@karrisaarinen

A common dynamic I observe with AI: it feels most impressive when you don’t know much about the subject, don’t care or don’t have a clear idea of what the you want. This applies across design, code, legal, and more. If I don’t know code very well, every piece of code it writes feels very impressive. Once you know what something should feel or look like, it becomes almost impossible to guide AI there. And you definitely can’t one-shot it.

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Siddharth M@sgm_force·
RT @GaryMarcus: “AI: it feels most impressive when you don’t know much about the subject, don’t care or don’t have a clear idea of what the…
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Karri Saarinen
Karri Saarinen@karrisaarinen·
A common dynamic I observe with AI: it feels most impressive when you don’t know much about the subject, don’t care or don’t have a clear idea of what the you want. This applies across design, code, legal, and more. If I don’t know code very well, every piece of code it writes feels very impressive. Once you know what something should feel or look like, it becomes almost impossible to guide AI there. And you definitely can’t one-shot it.
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World of Statistics
World of Statistics@stats_feed·
Alcohol is the leading global risk factor for premature death and disability among people aged 15–49, causing more deaths than malaria, tuberculosis, and violence combined.
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Dr Alexander D. Kalian
Dr Alexander D. Kalian@AlexanderKalian·
Every time I tell AI utopianists that biology is too complex for AI to "solve", they cite the success of AlphaFold. No, AlphaFold did not "solve" protein folding. It gets broad structures correct ~70-88% of the time (depending on evaluation), enabling useful but flawed statistical guesses. True "solving" would require ~99.9%+ accuracy, practically zero meaningful edge cases, and high confidence across fine details like side chains and conformations. Even then, this is just one narrow slice of the complexities of proteomics. The persistent gap between the "AlphaFold solved protein folding" claim and reality is a perfect example of AI overhype in biology.
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