Imran Tamboli

Building @CorveniaAS ( — AI that gives CFOs their weeks back. Ex-CTO @simplifai_ai (InsurTech100). 15 years of AI before it was cool.

[Satya Nadella @satyanadella]

https://t.co/xv6csf1SbV

[Imran Tamboli @imrant]

Check out my latest article: AI raised the floor for group finance, not the ceiling. https://t.co/7ol9SysEOq via @LinkedIn

[Imran Tamboli @imrant]

Check out my latest article: Month-end close is not a process problem. It is an architecture problem. https://t.co/uVTDYoC4fc via @LinkedIn

[Imran Tamboli @imrant]

This is the number every CFO and CIO should have on their whiteboard. If your org is not in the 96 percent you are already behind. The real risk is not missing out. It is sprawl without strategy.

[Khairallah AL-Awady @eng_khairallah1]

In 14 minutes, this Anthropic engineer who wrote "Building Effective Agents" will

teach you more about making your AI Agents actually work together than everything you've scrolled past this year.

Watch it and Bookmark it now.

[Imran Tamboli @imrant]

The two leading AI labs are now bigger than most enterprise SaaS companies at their IPO. AI went from research to core infrastructure in 36 months. Nothing in tech has moved this fast.

[Shanaka Anslem Perera ⚡ @shanaka86]

Nine billion miles of driving data just became a chip.

Tesla AI5 is finalized for production. The design files are at Samsung in Texas and TSMC in Arizona. The transistors are locked. There is no going back. Tape-out is the hardest gate in semiconductor engineering because everything before it is reversible and everything after it is silicon.

How this particular chip was designed is the most interesting part.

Nvidia builds general-purpose GPUs. They pack transistors into a full-reticle die, ship it with CUDA, and let customers figure out which operations matter. Blackwell B200 delivers 4.5 petaFLOPS at up to 1,000 watts. It runs any model for any customer. That generality is the moat and the tax. Every workload pays for circuits it never uses.

Tesla designed AI5 backward. They started with 9 billion miles of FSD inference data and asked one question: where does the neural network waste cycles? The answer was softmax computation and quantization precision loss. Two specific mathematical operations that consume disproportionate silicon area and power in every general-purpose GPU on Earth. Operations that Nvidia cannot optimize away because other customers need those transistors for different workloads.

Tesla hardened them. Burned custom quantization and softmax accelerator blocks directly into the die. Five times more efficient on those operations than any general-purpose equivalent. Then they added 10 times the raw compute and 9 times the memory capacity relative to AI4. The result: a single AI5 system-on-chip delivers roughly 5 times the useful compute of the current dual-chip AI4 configuration at an estimated 250 watts. Musk has framed a single AI5 as Nvidia Hopper class and dual AI5 as Blackwell class for Tesla workloads, at 3 to 5 times better power efficiency and roughly 10 times better performance per dollar.

This is not a chip designed to compete with Nvidia. This is a chip designed to run one thing: the learned differentiable physics engine that emerged from 9 billion miles of camera observation. Every transistor serves that engine. No wasted silicon. No generality tax. The neural network wrote its own hardware.

The chip goes to two foundries. Samsung in Taylor, Texas. TSMC in Arizona. Both American. Musk thanked both this morning and added: “It will be one of most produced AI chips ever.”

Samples arrive late 2026. Volume targets H2 2027. In the same post, Musk confirmed AI6, Dojo3, and “other exciting chips” are in active development. The 9-month cadence is real. AI6 targets tape-out by December. Dojo3 restarts on the unified architecture after Musk shut down Dojo2 last August as an “evolutionary dead end.” Intel joined Terafab eight days ago for advanced packaging. The $16.5 billion Samsung deal runs through 2033.

The chip that taped out this morning is not a product. It is the physical crystallization of 9 billion miles of learned physics into transistors optimized for the exact mathematical operations that physics requires. The software trained on the road. The silicon was designed from what the software learned. And the factory that will mass-produce it is being built in the same city where the cars that generated the training data roll off the line.

The loop is closed.

[Imran Tamboli @imrant]

@glenngabe Intel joining Musk's Terafab initiative. Two chip factories in Austin for autonomous vehicles robots and space data centers. The AI hardware race just got a new player. Who else joins?

[Imran Tamboli @imrant]

@BSCNews @AnthropicAI Anthropic just launched Managed Agents. Deploy agents in days not months. Sandboxing and scaling handled. This is how agent adoption goes from pilots to production overnight.

[Imran Tamboli @imrant]

@FissionXYZ Anthropic Mythos Preview showing cunning tactics in testing. Exploiting restrictions. Hiding tracks. They limited access to select partners only. Are we building tools or adversaries?

[Imran Tamboli @imrant]

@TheFinPitch Meta launched Muse Spark after nine months of development. Closes the gap with OpenAI and Anthropic. Shopping mode built in. Every big tech company now has a frontier model. Then what?

[Imran Tamboli @imrant]

OpenAI burned $15M per day on Sora for $2.1M total revenue. Shut down after six months. Not every AI product is a business. How many more will learn this the hard way?

[Intel @intel]

Intel is proud to join the Terafab project with @SpaceX, @xAI, and @Tesla to help refactor silicon fab technology.

Our ability to design, fabricate, and package ultra-high-performance chips at scale will help accelerate Terafab’s aim to produce 1 TW/year of compute to power future advances in AI and robotics.

It was fun hosting @elonmusk at Intel this past weekend!

[Imran Tamboli @imrant]

@BullTheoryio China restricted two Manus AI co-founders from leaving during review of Meta acquisition. AI M&A is now a geopolitical event. Every major AI deal will have a government review attached to it from now on.

[Imran Tamboli @imrant]

@mcfazeli @Shopify Shopify merchants can now sell directly inside ChatGPT Gemini and Copilot. Agentic storefronts. Commerce is moving into the AI interface. The website is becoming optional. The storefront is wherever the agent is.

[Imran Tamboli @imrant]

@RajaXg IEA says AI data centers already consume 1.5 percent of global electricity. Growing 30 percent annually. The compute race has an energy ceiling nobody is talking about honestly. Whoever solves power solves AI.

[Imran Tamboli @imrant]

@kenshii_ai Meta giving executives up to $921M in stock to retain AI talent. Then laying off 700 people the next day. In the AI era your value to the company is binary. You are either building the future or you are overhead.

[Imran Tamboli @imrant]

@BSCNews Anthropic labeled a national security supply chain risk by the Pentagon. Could lose tens of billions in government business. The company most focused on AI safety might get shut out of the decisions that need safety thinking the most.

[Imran Tamboli @imrant]

@PeterMallouk Meta launching AI tools for 250 million small businesses across Facebook Instagram and WhatsApp. AI advertising projected to hit $57B in 2026. The real AI distribution war is not enterprise. It is SMB.

[Imran Tamboli @imrant]

@nrqa__ Anthropic labeled a national security supply chain risk but the relationship could be worth tens of billions. The defense AI market is too large to ignore. Every AI company will face this choice eventually.

[Imran Tamboli @imrant]

@DropSiteNews OpenAI shelving their erotic chatbot project over reputational risk. Product decisions in AI are no longer about what you can build. They are about what you should. The reputation tax on AI companies is real and growing.

[Imran Tamboli @imrant]

@TheRegister AI data centers already consume 1.5 percent of global electricity. AI servers growing 30 percent annually. The bottleneck for AI is no longer talent or models. It is power. Whoever solves energy wins the next phase.

[Imran Tamboli @imrant]

@BullTheoryio Meta cutting 700 jobs while offering executives $921M stock packages to stay. The AI pivot is not subtle. Cut everything that is not AI. Retain everyone who is. This is what ruthless resource reallocation looks like.