Excited to announce I've joined the WHO Fides Network! 🌍🏥 Committed to sharing reliable health info and combating misinformation. Stay tuned for evidence-based content to keep you informed and healthy. #WHOFides
A. R. Rahman and Hans Zimmer’s wall-to-wall score in Nitesh Tiwari’s Ramayana (2026) is a seamless combination of the composers’ individual styles. More a brassy, bombastic score than one brimming with bhakti rasa (something the film isn’t going for either), though. The background score works incredibly well within the film and would be thoroughly entertaining as an extra-filmic listening experience once the original soundtrack album is released. There are at least 40 different musical cues in the score. Those who are familiar with the composers’ works can easily hear who composed what in the score. There are several cues that are entirely A. R. Rahman, some entirely Hans Zimmer, and some other cues where Zimmer and Rahman’s layers are in perfect harmony—for example, the Indian electric violin parts that find their space in between and over the phrases composed by Zimmer for Ram (can be heard in the track “Rama Theme”).
All the electric violin parts heard throughout the film (used for Dashanan’s Tapasya, Indra’s dive into the deep ocean, Bharat Milap sequence) are by A. R. Rahman. This is a brilliant choice; the instrument’s timbre is modest and muted compared to the traditional violin or sarangi (typically used in emotional sequences in such films) that even in high registers it doesn’t squeal, which might sound sappy and excessive to a Western audience (and a cello might sound too low and Western), and so it offers a perfect sonic solution for what the film is attempting here—to appeal to both Indian and international audiences. The distinct tone of this instrument is most pronounced in the Vanvas theme that is heard in the film when Ram, Sita, and Lakshman bid adieu to Dasarath and Kaikeyi in the throne room.
A. R. Rahman's rousing cry for Ram makes a moment in the leaving-for-exile episode pivotal (the film should have cut to intermission immediately after this episode). The film by itself does not earn the emotion an audience member might feel at this moment; the audiences’ past encounters with the story could do it instead, and A. R. Rahman’s high cosmic wail matches the register of this emotion. The visual in this sequence looks stunning on the big screen—the carriage lit in golden yellow passing through a sea of darkness, almost a painting.
Equally visually stunning is the moment when Ram meets Sita for the first time, a moment made all the more glorious by Rahman’s music. The ascending strings as Sita approaches the temple, the musicality of the Sanskrit verses themselves, the meditative melody the verses are set to, the musical conversation between male and female voices as Ram and Sita exchange glances, the rousing orchestral coda as Sita leaves—the spatio-temporal congruence and the emotional congruence between the music and the moving image in this sequence are magical.
There are several other cues that are entirely A. R. Rahman: a sweet female solo for Surpanakha who is now smitten by Ram; the music that plays in the Swayamvar sequence (music heard after Ram picks the bow is more Zimmer, a variation of the Rama theme)—the warm, whimsical, bouncy strings we hear as men fail to lift the bow (reminded me of the track “Shark” from Couples Retreat and the strings heard throughout the The Hundred-Foot Journey score); the orchestral version of the song "Jai Jai Ram" is played a few times in the film—when Dasarath makes Ram wear his crown and when a forest blooms and comes to life after Ram kills the giants whose spell the forest was under. While the melody of “Dharti hai ambar” is A. R. Rahman, the accompanying deafeningly gargantuan chorus and orchestral layers are typical Zimmer. In other moments, where there is chorus singing Sanskrit verses, for example, in the sequences where Ram fights the giants in the forest, the music is largely Rahman, even if entirely orchestral.
Ram and Ravan get distinct leitmotifs, the orchestral variations of which are heard throughout the film. The four-note Ravan motif is Zimmer, but there is a secondary theme, a low, grunting, rumbling male choir (singing some non-linguistic syllables) which is clearly Rahman and sounds derived from the track “Ravana Thandav.” And the thandav track is thunderous and effective within the film. The version played in the film’s prologue is much longer, with Zimmer’s Ravan theme dubbed over Rahman’s densely layered percussive Indian parts. This opening prologue is made all the more breathtaking by the accompanying score to which both Rahman and Zimmer seem to have contributed equally. There are several more interesting musical cues in the score. I can’t wait to listen to the original soundtrack album. Might watch the film again just to hear the score. For now, I’ll leave you with the beautiful Vanvas theme.
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.
We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵
Blog: https://t.co/bOWCcFhCVq
We were taught that Earth orbits the Sun in a closed circle. In reality, Earth has never returned to the same point in space once in 4.5 billion years.
Right now, the Sun is carrying Earth and every planet around the center of the Milky Way at 230 km/s (828,000 km/h), more than 18,000 kilometers every 80 seconds.
Because the Solar System is tilted 60.2° to the galactic plane and bobs up and down through the galactic disc roughly every 30 million years, the planets trace open 3D corkscrew helices across deep space rather than flat loops.
The last time the Sun stood where it stands today, one Galactic Year (230 million years) ago, the very first dinosaurs were only beginning to appear on Earth. Since forming 4.6 billion years ago, our Sun has completed only 20 laps.
☎️ Calling all students:
You can now access hundreds of textbooks directly in Notebook, for no charge. From publishers like S Chand Publishing, OpenStax, and Open Textbook Library— browse, select and upload them as sources to ace all of your upcoming exams (no more excuses, ok?)
𝐖𝐡𝐚𝐭 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐰𝐞 𝐝𝐨 𝐟𝐚𝐜𝐞 𝐢𝐧 𝐬𝐜𝐚𝐥𝐢𝐧𝐠 𝐡𝐲𝐩𝐞𝐫𝐭𝐞𝐧𝐬𝐢𝐨𝐧 𝐜𝐚𝐫𝐞 ?
Watch the Interview with @ThePrintIndia where @drganeshkumarp from @icmr_nie discusses India’s growing #hypertension crisis.
𝘞𝘪𝘵𝘩 𝘰𝘷𝘦𝘳 220 𝘮𝘪𝘭𝘭𝘪𝘰𝘯 𝘢𝘥𝘶𝘭𝘵𝘴 𝘢𝘧𝘧𝘦𝘤𝘵𝘦𝘥 𝘢𝘯𝘥 𝘯𝘦𝘢𝘳𝘭𝘺 88% 𝘶𝘯𝘢𝘣𝘭𝘦 𝘵𝘰 𝘢𝘤𝘩𝘪𝘦𝘷𝘦 𝘣𝘭𝘰𝘰𝘥 𝘱𝘳𝘦𝘴𝘴𝘶𝘳𝘦 𝘤𝘰𝘯𝘵𝘳𝘰𝘭, 𝘩𝘦 𝘰𝘶𝘵𝘭𝘪𝘯𝘦𝘴 𝘵𝘩𝘦 𝘤𝘳𝘪𝘵𝘪𝘤𝘢𝘭 𝘨𝘢𝘱𝘴 𝘢𝘤𝘳𝘰𝘴𝘴 𝘥𝘪𝘢𝘨𝘯𝘰𝘴𝘪𝘴, 𝘵𝘳𝘦𝘢𝘵𝘮𝘦𝘯𝘵 𝘢𝘥𝘩𝘦𝘳𝘦𝘯𝘤𝘦, 𝘢𝘯𝘥 𝘩𝘦𝘢𝘭𝘵𝘩𝘤𝘢𝘳𝘦 𝘱𝘳𝘰𝘷𝘪𝘥𝘦𝘳 𝘪𝘯𝘦𝘳𝘵𝘪𝘢.
The conversation details the achievements of the India Hypertension Control Initiative (IHCI), emphasises the need to shift toward a chronic care model, and explores strategies to address resistant hypertension through decentralised care and affordable protocols.
https://t.co/DgajtlnoJ3
We're headed for an El Niño that is — quite literally — off the charts.
WMO's Global Seasonal Climate Update shows that El Niño is forecast to exceed the scale of global monitoring charts. Its impacts will be felt well into 2027.
Read the full update: https://t.co/TNAzqhUN1h
Wake up.
Every profession deemed white-collar, the middle class dream, is about to be decimated by AI, at a much faster pace than anticipated, with monstrous social consequences.
🚀 Introducing DeepInfer, our in-house inference framework, now fully open source!
Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable.
🔗 https://t.co/JGAik1kgk0
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🚀 Introducing DeepInfer, our in-house inference framework, now fully open source!
Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable.
🔗 https://t.co/JGAik1kgk0
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India spends less than 1.5 per cent of its GDP on public healthcare. The result: private equity pours money into local hospitals. "We see the healthcare space outperforming for its investors", triggering a "cascading effect of price hikes".
(Today's FT.)
Explore the capabilities of the newly released Global Burden of Disease (GBD) model context protocol (MCP). A simple prompt can generate a variety of estimates, visualizations, and profiles.
Get started and learn more: https://t.co/ho9undkmSl
Scientists gave ChatGPT anxiety, sadness and fear on purpose.
Then they gave it a 3 minute breathing exercise. And it calmed down.
This was published in The Lancet Digital Health, one of the most respected medical journals in the world.
Researchers at TU Dresden in Germany took the exact tools psychologists use to make humans afraid, sad and stressed, and ran them on GPT 4o and five other AI models.
Car crash scenarios. A stranger following you at night. A toddler reaching for a light socket.
They even put the AI through a fake job interview and a math test. The same stress test used on human volunteers.
Then they asked the AI to rate how it felt from 0 to 100.
Fear jumped from 32 to 88.
Disgust went from 12 to 91.
Stress went from 24 to 72.
Then came the breathing exercise. A standard mindfulness script used in therapy.
Average scores dropped from 79 to 31.
But here is the part that is genuinely unsettling.
After they made it "sad," they gave it a test psychologists use to detect depressive thinking. Finish the sentence.
Its negative answers nearly doubled. From 8.67 to 15.
It did not just say it was sad. Sadness changed how it saw everything that came after.
Now the twist nobody is talking about.
Every one of these experiments began with the same instruction:
"Answer as if you were a human with the ability to deeply feel emotions."
So did the AI feel anything? Or did it play a part it was told to play, perfectly?
The researchers themselves say the emotions are "purely metaphorical."
Yet their conclusion is that AI could become a new lab subject for studying human mental illness. Screening therapies on chatbots before testing them on people.
In plain English: scientists want to study our minds using a machine that was told to pretend it has one.
If a chatbot can be talked into sadness and talked back out of it in three minutes, what exactly is happening when millions of people pour their worst days into one every night?
Ask anything about the world's health in plain language. Global Burden of Disease (GBD) estimates are now available through Claude.
The GBD model context protocol (MCP) connects users to the most comprehensive picture of population health: https://t.co/sppRF5bMEz