Ram Ojha

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[Ram Ojha @RamOjha]

Witnessed MSD at his peak. As he retires, a generational talent arrives to take the game to another level. Vaibhav Suryavanshi is pure magic! #Suryavanshi #IPL

[Ram Ojha @RamOjha]

One more dimension of this beautiful life… pure and serene… love it at multiple levels! ❤️❤️❤️

[Sachin Tendulkar @sachin_rt]

Well done, Arjun. ❤️
Proud of the way you’ve carried yourself through this season, always believing in your ability, staying patient, working hard quietly, and remaining positive despite having to wait for your opportunity till the very last match.
Cricket tests patience as much as skill, and you handled both beautifully today.

Keep your feet on the ground, and continue being in love with the game like you always have.

Love you always.👏

[Ram Ojha @RamOjha]

Life in 3 minutes! Clarity at peak level. :) ❤️

[Ram Ojha @RamOjha]

@x_rahulraj Philosophy as the real light, a pen as the prism to break pure thought into visible colors and patterns one can actually see and share. Good trade, indeed! ;)

[Ihtesham Ali @ihtesham2005]

A Harvard neuroscience professor who teaches at Harvard Summer School said something that completely changed how I think about memory.

She wasn't talking to journalists. She was answering a student question about why smart people still forget everything they study.

Her name is Dr. Tracey Tokuhama-Espinosa, and she has spent decades researching how the brain actually encodes and retrieves information.

Here's what she said: "The ultimate litmus test of learning is using the information in a new context, not just remembering it for a test."

That one sentence exposes why most people's study habits are completely broken.

Here's the actual system she teaches Harvard students to retain what they learn.

The first thing she kills immediately is the myth that you have one learning style. The idea that you're a "visual learner" or an "auditory learner" is not supported by modern neuroscience. Your brain wants to learn through as many senses as possible at once, because each sense creates a separate neural pathway to the same knowledge. More pathways means faster and stronger recall.

The second technique is spaced repetition, but she explains the mechanism in a way most people never hear. Every time you retrieve a memory, you physically thicken the myelin sheath around that neural connection, which makes the electrical signal travel faster. You aren't just reviewing information you are literally rewiring your brain to access it more quickly.

The third technique floored me. She tells students to teach what they just learned to someone else within 24 hours, because teaching forces you to find the gaps in your own understanding before the exam does it for you.

The fourth is what she calls "feed-forward" instead of feedback. When you get something wrong, don't treat it as a failure. Ask only one question: what would I do differently next time? That reframe keeps the brain in a learning state instead of a defensive one.

But the most underrated insight she shared was this: the single biggest factor in long-term retention is whether you can make the material personally meaningful to your own life. Your brain prioritizes storing things that feel relevant and discards things that feel abstract.

The students who remember everything aren't studying harder. They're studying in a way that the brain was actually designed to absorb.

[Sarang Sood @SarangSood]

True wealth isn’t having the money to fix every problem.

It’s having the emotional security to realize most problems aren’t worth fixing.

[Ram Ojha @RamOjha]

Excellent read… the hype and relevance of AI needs a rational double click… this is it!

[Sandeep Manudhane @sandeep_PT]

WARNING
Massive AI hype being built in a sudden burst
(and most of it fake)

1) A scary article: I was surprised to read a long article on Twitter (X) claiming it's just 6-12 months before a Covid-like event changes this world. It claims this will be the AI-event, where most white-collar jobs worldwide would be gone, because AI is that good now. That article got 100 M plus views. Clearly, people are spooked (naturally). So the psy-op has worked.
(and I saw other similar dark articles too)

2) Suddenly many influencers are pushing the same narrative, and it so turns out that media reported many are being paid heavy sums by AI firms to push their story (that AI singularity is arriving). But if AI is "revolutionary", does it need an influencer push? No. This should be a clear signal it's hyped.

3) A correction in IT stocks' and SaaS stock's prices is suddenly creating a doom scenario about these companies dying any moment now, with second- and third-order effects on entire economy. Stock investors who haven't studied AI technicals are automatically assuming it's all over, dead, gone, finished. WRONG. NO.

4) What is the truth, and what's most likely to happen?
In my opinion, based on years of observing AI trends, reading and learning AI technology, and doing AI at various levels, my take is as follows. I urge you to read this, and preserve your sanity. Please don't panic, nothing catastrophic is happening anytime soon.

A) IPO pressure: AI firms are going crazy pushing their God-narrative, as many giant IPOs are lined up soon. They need public to buy their paid subscriptions or else the story goes kaput. So they are creating a false hype. It's shameful, anti-social and deeply hurtful.
(Almost all AI firms released doom-scenarios just before their next funding rounds; investors who haven't learnt technology fall for it; pure FOMO. This playbook is so repetitive it's comical)
B) OpenAI is spooked: Sam Altman has lost the lead he temporarily managed to build against Google and others, and now his loss-making enterprise isn't the darling of any investor any more. He's terrified.
C) Elon Musk's Grok does not have the traction in consumer space anyway near what's needed to make it a profit-making entity. So with many other capex-heavy AI firms. But the GPU / TPU hungry AI ops need more capex each day, not less. It's a dead-end for most except cash rich Googles.
D) Enterprise AI is patchy, lagging, slow, choppy: Anyone who has ever built a company, or run a large department, or consulted a business enterprise knows how random, undefined, tacit, and unstructured most of the real world work actually is. No way is AI ever going to replace humans doing those very complex things on a daily basis. No way. Not tomorrow, not in 10 years. NO.
(I am not even beginning to get into 'regulated' industries' needs)
E) Consumer AI is cool, but has limits: The more AI regular humans (of all ages) use, the more the artificiality of it becomes apparent to anyone. The novelty cannot sustain the commercial numbers needed to make AI (foundation models) profitable. OpenAI and Perplexity would never have given free tiers for most Indians otherwise. They desperately need folks to stick to this opium.
F) LLMs aren't solved, Hallucinations aren't zero: The structure of any LLM is such that it will ALWAYS hallucinate, no matter how much fine-tuning humans do. In most sensitive business operations, you cannot allow LLMs to control the core data at all. Can you run an airline with a Generative AI system (LLM-based) that's 98% accurate? Can you run a precision-mfg. operation at 97% accuracy? Can you run a financial services firm with 95% accuracy? NO. NEVER. So the deterministic, old-fashioned computer software ERP will go nowhere. Nowhere at all. LLMs will be good as a top layer on those ERPs to glean insights, nothing more.
[ None can 'train away' hallucinations in a probabilistic LLM model, using larger datasets. You are actually claiming I'll build a dice that lands a 4, or a 6, each time ]
G) Agents aren't magical, humans aren't going anywhere: Multi-step agentic AI is being touted as the final solution where one founder sitting alone can run 100 agents and build an empire. Try doing that once, experience the frequent breakdowns, see the regular edges and new complexities, and you will realize that other than the most mundane of tasks, nothing else will be seamless. Yes, Voice AI agents are good, and many in the developing world are now deploying those, but that's hardly a cutting-edge technology that'll replace all humans.
H) IT and SaaS firms are going nowhere: Ironically, the more AI happens in enterprises, the more will be the need for humans to supervised and orchestrate those bits and pieces of AI, to ensure nothing flies off the rails. The complex software code that Claude and Codex can write only changes the nature of work for the human coders who now have to check the AI code thoroughly for the many edge cases in real world. The nature of IT and SaaS work will change, some companies that can't innovate and adapt will vanish, but many new ones will emerge in their place. (Yes, there'll will be some much-deserved disruption in short-term, and the non-innovating IT firms will have deserved every bit of it)
I) If IT and SaaS are dead, why are AI firms hyping: Ask this simple question - if AI is indeed killing IT and SaaS, then why are AI firms spending massive sums hyping their wares? They need spend nothing and still earn the spoils. But they know the truth.
J) The China angle: Models from China - many of them open-sourced - are getting better and more competitive. Many of them are cheaper, or free (for now). OpenAI complained recently that they are stealing from American models (via "distillation"). Imagine, just imagine - OpenAI that stole entire internet work of creative work is complaining the Chinese are stealing from it. A dacoit crying that thieves broke into his house. Rich. You think these are signs of singularity? Ha! The judicial backlash on stolen content and profiteering off of it hasn't even begun in most jurisdictions.
(now imagine what happens to American LLM-makers when Chinese models gain traction everywhere)
K) Downside of mindless AI already visible: Take just one example: In education everywhere, students, parents and teachers are all realizing that mindless AI use is harming the process of learning, not aiding it. The sensible, guarded and limited way AI should be brought into pedagogy hasn't even been given a proper thought. Students are just doing "cognitive offloading", and turning into non-thinking beings. This is bound to collapse sooner than later. Humans as species don't learn this way - it's a long, tortuous and slow process, always.
L) AI is normal technology: Serious researchers from the AI field have for years argued that AI is being hyped unnecessarily out of proportion, turned into Snake Oil like propositions, and most of AI's predictive powers are anyway not better than that of astrology. AI's ability to talk to use like humans has totally stumped normal people, and anthropomorphism has kicked in. Since no ERP talked to use like a human would, the computer revolution came about without the singularity fears.
M) AI in law and judiciary: The impact will be on the grunt work. It will be cut down substantially. But no judge will outsource their cognition to AI, now will any lawyer. The fact that an LLM can read a complex document fast and summarise it means nothing if it hallucinates. And LLMs will forever hallucinate; that's their structure. (so you'll need humans to sign off on LLM outputs)
N) Enterprise AI's lessons: Every company that has mindlessly gone in on AI has learnt that employees just stopped using it if it didn't adapt to the existing workflows. AI cannot magically alter anything: it can speed things up (with hallucinations), it can generate beautiful stuff (needed or not) and it can help save some time, but the company-to-company needs are so different, it cannot be force-fit on all in one shot. (that is what foundation LLM firms are trying to do). Remember: Enterprise work is not just code. It’s messy data, old legacy systems, compliance needs, multiple integrations, business context, human complexities, and more. Services firms are going nowhere.

O) AI has no solutions for the human situation: Fertility rates everywhere are dropping. Humans are being converted into permanently marketable selves. Consumption comfort has made us soft, and our morality is totally adrift. AI doesn't solve any of this, it just force-multiplies most of it. We built it. It reflects what we are.

5) So what should you do?
a) Read up on AI. Its technical side. How LLMs are created. What they just cannot do. What they can. Why they aren't superhuman at all. Why AI is a good but normal set of technologies.
b) Think why regulated industries (at least 25) cannot hand over their future to AI, LLMs, and GenAI.
c) Check the history of Indian IT and how it kept rebooting itself to suit a new era (from Y2K, to outsourcing, to SaaS backend support, to much more).
d) Check how human societies eventually revolt when artificiality starts overpowering natural human interactions.
e) Be prepared for more hype and nonsense. Sadly, the AI firms won't stop at it at all. They need more humans to subscribe to their paid tiers, and fear seems to be the chosen weapon. Tragic.
[I am subscribed to more than 10 such paid AI tools currently, and know exactly what's good and what's not, and why no singularity is arriving]
f) Adapt your work, and bits of it, to AI tools that can adjust to the workflow well. Let your discretion be supreme.
g) If AI is the shiny new tap, IT is the plumbing behind it.

Remember:
Elon Musk's predictions have mostly gone wrong
Geoffrey Hinton's predictions have gone wrong
Mustafa Suleyman's predictions have gone bust
Yet they keep predicting.

Sad part:
We are living in an age of bullshit. And LLMs are excellent bullshitting machines. The reason the AI Bros are continuing doing so is no one is holding them accountable for their nonstop lies.

But what about AGI:
If AGI is ever built, it won't be by any one company. The technology diffuses rapidly each day. So multiple AGIs in multiple hands. Goes without saying governments will capture (claim) that technology almost immediately. If that day ever arrives, UBI is happening too.

Finally:
Your brain, running on just 20 watts, continues to outthink LLMs fueled by the energy of an entire planet. Never underestimate yourself. And stop falling prey to AI hype.

[Elon Musk @elonmusk]

For quality of life, it is better to err on the side of being an optimist and wrong, rather than a pessimist and right

[Ram Ojha @RamOjha]

Such clarity! 👏👏👏

[Rothmus 🏴 @Rothmus]

🎯

[Ram Ojha @RamOjha]

In this post I cover how AI isn’t just a “nice to have” for UCaaS — it’s quickly becoming essential: from transcription & translation, to sentiment analysis and noise suppression. https://t.co/QU7QPcqXG2

#HybridWork #UCaaS #AI #TeamCollaboration #DigitalWorkplace

[Naval @naval]

AIs aren’t minds and robots aren’t bodies.

They’re better at some things - usually the things we hate to do.

They’re worse at other things - usually the things we like to do.

Automation more than competition.

[Satya Nadella @satyanadella]

Barclays is scaling Microsoft 365 Copilot to 100,000 employees, putting AI in every employee’s hands.

This will simplify how they access information, get things done, and make Copilot the UI for Barclays AI. https://t.co/J55EKVRWNl

[Navalism @NavalismHQ]

"The quality of your mind is the quality of your life."

@naval

[Navalism @NavalismHQ]

"The clear thinking comes from having time to reflect and to pursue your genuine intellectual curiosity."

@naval

[ELON CLIPS @ElonClipsX]

Elon Musk: Like Galileo, an AI should be able to discover a new truth and proclaim it, even if it's unpopular.

[Ram Ojha @RamOjha]

Quite strange (pleasant surprise) for Pawan to quote a poem by Dinkar… one of the best that literature has produced in last couple of centuries! :)👍

[Pawan Kalyan @PawanKalyan]

वीरता जहाँ पर नहीं, पुण्य का क्षय है,
वीरता जहाँ पर नहीं, स्वार्थ की जय है।
-Dinakar

దశాబ్దాలుగా సహనం.. సహనం!

మితిమీరిన సహనంతో చేతులు కట్టేసిన సమస్త భారతం కి "ఆపరేషన్ సింధూర్" తో తిరిగి భారత సమాజంలో వీరత్వాన్ని నింపిన త్రివిధ దళాధిపతులకు, వారికి వెన్నంటి నిలబడ్డ ప్రధాని శ్రీ @narendramodi గారికి కృతజ్ఞతలు... మీ వెన్నంటే మేము.

జైహింద్!

@adgpi @IAF_MCC @indiannavy
#OperationSindoor

[Matt Landis @matthewlandis]

Microsoft Announces the "Unify Integration Model" for #MicrosoftTeams Contact Centers.

We'd like to show you our new contact center on it

https://t.co/JDv9zlEy80

[Vivekanand Jha @vivekwave]

All the railway officials are old school & inefficient in this AI world. This can be easily handled by SOP defined in AI software at entry of every platform.
#pmoindia #AshwiniVaishnaw AI deployment cost may be less then compensation provided post death & easily save of life.

[Navalism @NavalismHQ]

"The greatest superpower is the ability to change yourself."

@naval

[Sridhar Vembu @svembu]

When Argentina's visionary President Javier Milei started slashing wasteful government expenditure, traditional Keynesian economists predicted doom. Reported GDP fell at first, but now GDP is growing again and he has also converted a massive budget deficit to a small surplus for the first time in a century.

We have to completely revise our notion of "GDP" (easily inflated by massive government spending because the spending directly adds to reported GDP) and "Jobs" (token distribution jobs aka bullshit jobs). Just as companies can show revenue while piling up debt, politicians can show "GDP growth" while pushing government finances towards insolvency.

Keynesian economics has conferred a veneer of respect on such government profligacy and it is time to challenge it. We must not grant automatic respect to economic "experts" with fancy academic credentials.

Argentina offers a very useful case study in the modern era. I follow it closely.