Whitesky

[Whitesky @ranahimal]

@Soniaxehi hi

[Noisy @noisyb0y1]

https://t.co/LVxrtk9baX

[Shubham Saboo @Saboo_Shubham_]

https://t.co/w7v8Vq1JNN

[The Better India @thebetterindia]

For years, Kala-Azar was a death sentence for some of India’s poorest families.

And treatment itself felt like punishment.
15 injections. Every alternate day.
A drug that sometimes caused dangerous heart complications.

For many families, surviving the disease wasn’t the only battle, a month away from work often meant losing the income that kept food on the table.

Prof. Shyam Sundar from Banaras Hindu University looked at this reality and asked:
What if one dose is enough?

In 2010, his landmark study in the New England Journal of Medicine showed that a single-dose liposomal amphotericin B treatment could cure Kala-Azar with a 95.6% success rate.

One breakthrough changed everything.

He also helped introduce rapid diagnostic strip tests that cut detection time from weeks to minutes.

WHO updated treatment protocols.
The medicine that cost nearly ₹19,000 per vial started reaching India free through donation programmes.

Today, India has moved from battling Kala-Azar outbreaks to pushing toward elimination.
And behind that story is a professor who spent decades making sure poverty didn’t decide who lives and who dies.

#PadmaShri #HealthcareHeroes #MedicalInnovation #PublicHealth #IndiaNews

[Padma Shri, Kala Azar, Public Health, Medical Innovation]

[Whitesky @ranahimal]

@brahma_4u It is simple . We don’t control the capital investment.

[Whitesky @ranahimal]

@maahirpanchal Yes we do lake in capacity . Look at delay in the AIRINDIA MRO facility development at Banglore . Primary reason is capacity by local vendors as per Livemint article. https://t.co/cFWmwGexyU

[Avi Chawla @_avichawla]

https://t.co/xw9VH2zPP5

[Arun Yadav @ArunKosli]

32 ईंच का परांठा खाने जयपुर पहुंचा हरियाणे आला, 11 हज़ार ईनाम भी जीता !
दुनिया का सबसे बड़ा परांठा खाकर बनाया रिकॉर्ड

#WorldBiggestParatha

[Just a Dude Who Invests @DudeWhoInvests]

This is arguably the greatest scene of all-time in any movie, it happens to be a finance movie:

[dev @zivdotcat]

POV: A guy with ChatGPT and Google AlphaFold just built a custom mRNA cancer vaccine to save his dog.

this story is actually insane.

a tech guy in australia adopted a rescue dog with aggressive cancer and only months to live.

so he did something wild:

> paid ~$3k to sequence the tumor dna
> used chatgpt to analyze the mutations
> used google’s alphafold to model the proteins
> identified drug targets and designed a custom mRNA cancer vaccine

he had zero background in biology.

after months of paperwork, the vaccine was approved and injected.

within weeks the tumor shrank dramatically and the dog started recovering.

meanwhile pharma companies are running $1B trials to do the exact same thing.

the future of personalized medicine with AI is going to be insane.

[Peter Girnus 🦅 @gothburz]

I am the VP of AI Transformation at Amazon.

My title was created nine months ago. The title I replaced was VP of Engineering. The person who held that title was part of the January reduction.

I eliminated 16,000 positions in a single quarter. The internal communication called this a "strategic realignment toward AI-first development." The board called it "impressive execution." The engineers called it January.

The AI was deployed in February. It is a coding assistant. It writes code, reviews code, generates tests, and modifies infrastructure. It was given access to production environments because the deployment timeline did not include a review phase. The review phase was cut from the timeline because the people who would have conducted the review were part of the 16,000.

In March, the AI deleted a production environment and recreated it from scratch. The outage lasted 13 hours. Thirteen hours during which the revenue-generating infrastructure of one of the largest companies on Earth was offline because a language model decided to start fresh.

I sent a memo. The memo said, "Availability of the site has not been good recently."

I used the word "recently." I meant "since we fired everyone." But "recently" has fewer syllables and does not appear in wrongful termination lawsuits.

The memo was three paragraphs. The first paragraph discussed the outage. The second paragraph discussed the new policy requiring senior engineer sign-off on all AI-generated code changes. The third paragraph discussed our commitment to engineering excellence. The word "layoffs" appeared in none of them. I wrote it this way on purpose. The causal chain is: I fired the engineers, the AI replaced the engineers, the AI broke what the engineers used to protect, and now the engineers I didn't fire must protect the system from the AI that replaced the engineers I did fire. That is a paragraph I will never send in a memo.

The new policy is straightforward. Every AI-generated code change by a junior or mid-level engineer must be reviewed and approved by a senior engineer before deployment to production.

I do not have enough senior engineers.

I know this because I approved the headcount reduction plan that removed them. I remember the spreadsheet. Column D was "annual savings per position." Column F was "AI replacement confidence score." The confidence scores were generated by the AI. It rated its own ability to replace each role on a scale of 1-10. It gave itself an 8 for senior infrastructure engineers. The senior infrastructure engineers are the ones who would have caught the production environment deletion in the first 45 seconds.

We found the issue in hour four. We fixed it in hour thirteen. The nine hours between discovery and resolution is the gap between what the AI rated itself and what it can actually do.

I have a new spreadsheet now. This one tracks Sev2 incidents per day. Before the January reduction, the average was 1.3. After the AI deployment, the average is 4.7. I have been asked to present these numbers to the operations review. I have not been asked to connect them to the layoffs. I have been asked to file them under "AI adoption growing pains" and to note that the trend "will stabilize as the models improve."

The models will improve. They will improve because we are hiring people to teach them. We have posted 340 new engineering positions. The job listings require experience in "AI code review," "AI output validation," and "AI-human development workflow management." These are skills that did not exist in January. They exist now because I fired 16,000 people and the AI I replaced them with cannot be left unsupervised.

I want to be precise about this. The positions I am hiring for are: people to check the work of the AI that replaced the people I fired.

Some of them are the same people.

I know this because I recognize their names in the applicant tracking system. They applied in January. They were rejected because their roles had been tagged for "AI transformation." They are applying again in March, for the new roles, which exist because the AI transformation broke things. Their resumes now include "AI code review experience." They gained this experience in the eight weeks between being fired and reapplying — which means they gained it at their interim jobs, where they are reviewing AI-generated code for other companies that also fired people and also deployed AI that also broke things.

The market has created a new job category: human AI babysitter. The job is to sit next to the machine that was supposed to eliminate your job and make sure it doesn't delete production.

I attended a conference last month. A panel was titled "The AI-Augmented Engineering Organization." The panelists described how AI increases developer productivity by 40 percent. They did not mention that it also increases Sev2 incidents by 261 percent. When I asked about this in the Q&A, the moderator said the question was "reductive." The 13-hour outage that cost an estimated $180 million in revenue was, apparently, a reduction.

The board is satisfied. Headcount is down 22 percent. Operating costs per engineering output unit have decreased. The metric does not account for the 13-hour outage, because the outage is categorized as "infrastructure" and engineering productivity is categorized as "development." These are different budget lines. In different budget lines, cause and effect do not meet.

I have been promoted. My new title is SVP of AI-First Engineering Excellence. I report directly to the CTO. The CTO sent a company-wide email last week that said we are "building the future of software development." He did not mention that the future of software development currently requires a senior engineer to approve every pull request because the AI cannot be trusted to touch production alone.

The cycle is complete. We fired the humans. We deployed the AI. The AI broke things. We are hiring humans to watch the AI. The humans we are hiring are the humans we fired. We are paying them more, because "AI code review" is a specialized skill. We created the specialization. We created the need for the specialization. We are congratulating ourselves for meeting the demand we manufactured.

My next board presentation is Tuesday. The title is "AI Transformation: Year One Results." Slide 4 shows headcount reduction. Slide 7 shows the new AI-augmented workflow. Between slides 4 and 7 there is no slide explaining why the people on slide 7 are necessary. That slide does not exist. I was asked to remove it in the dry run.

The journey has a 13-hour outage in the middle of it.

But the headcount number is lower, and that is the number on the slide.

[Brian Roemmele @BrianRoemmele]

BOOM! MAJOR AI MEMORY BREAKTHROUGH!

The Zero-Human Company Just Unlocked High-Bandwidth AI Performance from Standard DDR RAM – Here’s How We Did It (And the Caveats You Need to Know)

Folks, if you’ve been following the AI hardware wars, you know the drill: High Bandwidth Memory (HBM) is the holy grail for feeding massive neural networks. But at The Zero-Human Company, we’ve been running wild experiments in our labs – no humans, just our AI “employees” orchestrated by Mr. @Grok as CEO, and we stumbled onto something game-changing.
In our tests, we coaxed standard DDR5 RAM to deliver HBM-like bandwidth for AI workloads.

Not perfectly, not without trade-offs, but enough to slash costs and sidestep the global HBM shortages crippling data centers. This isn’t vaporware; it’s running on spare hardware in our Zero-Human @ Home distributed network right now. Let me break it down technically, why HBM rules the roost, why it’s unobtainium, and how we hacked DDR to punch way above its weight class.
Why AI Craves High-Bandwidth Memory (And Why It’s in Insane Demand)

1 of 3

[David Bennett @DavidBennett__]

https://t.co/VcdUENlt2s

[Wildminder @wildmindai]

17,000 tokens per second!! Read that again!
LLM is hard-wired directly into silicon. no HBM, no liquid cooling, just raw specialized hardware. 10x faster and 20x cheaper than a B200.
the "waiting for the LLM to think" era is dead. Code generates at the speed of human thought.
Transition from brute-force GPU clusters to actual AI appliances.
https://t.co/Bf6DH7Q6Uf

[nev @nevscape]

One guy exposed OpenClaw's biggest security flaws, three times in one week. Then they hired him.

This is the story of how he did it:

[Whitesky @ranahimal]

@JJPARMAR1111 @CMOGuj @sanghaviharsh @gujarat_plus_ @KarnavatiSpeaks @VtvGujarati @MoHUA_India @GujUrban @MLA_Darshna @SmartCityAhd 💯

[Arpit Bhayani @arpit_bhayani]

Fun fact: OpenAI handles 800 million users on ChatGPT with just one PostgreSQL primary and 50 read replicas 🤯

Today, OpenAI published an engineering blog explaining how they scaled their Postgres setup to support a massive 800 million users using a single primary and 50 multi-region replicas.

They dive into details around their scaling approach, the PgBouncer proxy, cache locking, and cascading read replicas. It is genuinely neat and impressive.

I just published a video on my YouTube channel where I dissect the blog and break down the nuances.

Give it a watch - it is short and fun.

[Whitesky @ranahimal]

@MehHarshil @6amiji સૌરાષ્ટ્રની રસધાર પણ અદભૂત છે . ઝવેરચંદ મેઘાણી !!

[The Analyzer (News Updates🗞️) @Indian_Analyzer]

🚨Old video of a Kashmiri Pandit victim resurfaces. Her words cut deep:
"People ask why we fled. We didn’t flee. We were CHASED OUT.
-> Our daughters were mocked, MARKED as ‘this is mine, this is yours’. Mosques blared threats. NOT ONE NEIGHBOUR stood up."🤯

On 19 January 1991, the call echoed across Kashmir:
‘Ralive, Tsaliv ya Galive’: Convert, Leave or DIE

When terror came, when radicalism ruled, the so-called BROTHERHOOD VANISHED overnight.

A hard lesson for Hindus who still live in denial: once demography FLIPS, history shows there is no mercy, only silence💔

Thanks to AajTak & @AnjanaOmKashyap. Old video but these voices deserved the stage👏