Tag: news

Weekend Notebook #2608 – India’s AI Moment: Capital, Compute, Confidence

amitabh apte
PM in a group photograph along with global tech leaders at the Opening Ceremony of India AI Impact Summit – 2026 at Bharat Mandapam, in New Delhi on February 19, 2026.

Published on LinkedIn and amitabhapte.com — 22nd February 2026

This Week in AI — India Moves from Talk to Build

Most global AI events feel like the same conversation, recycled. The India AI Impact Summit, from the coverage and announcements this week read differently.

Less vision decks. More committed capital. Less safety debate. More infrastructure.

Five days at Bharat Mandapam in New Delhi. Over half a million visitors. Twenty-plus heads of state. Nearly every major AI CEO in the world, Altman, Pichai, Amodei, Hassabis, in the same room. And a wave of announcements specific enough to take seriously.

The scale is worth stating upfront. Hyperscalers globally are on track to deploy $700 billion in AI capex this year. India pulled a significant share of that attention. Reliance announced $110 billion for data centres and infrastructure over seven years. Adani committed $100 billion for renewable-energy AI data centres by 2035. US tech added its own layer on top.

This was the fourth in the global AI summit series, following Bletchley, Seoul, and Paris. The previous three were dominated by safety debates. India changed the register deliberately. The theme: impact. Access. The Global South. That shift matters, I’ll come back to it.

What They Announced

Google committed $15 billion to build a full-stack AI hub in Visakhapatnam, gigawatt-scale compute plus a new subsea cable gateway to the US. Pichai framed it as becoming a “full-stack partner”, not a cloud vendor. Partnerships with Reliance Jio on a dedicated cloud region and with Indian research institutions on agriculture and climate were also confirmed.

Microsoft arrived with $50 billion earmarked for the Global South, India central to the plan. Its President Brad Smith told CNBC that India could develop its own frontier AI, in specific domains, and that there will be “a variety of different DeepSeek moments” to come, some of them from India. Its India President offered the sharpest line of the week: “AI will not kill jobs. AI will unbundle jobs.” Microsoft research shows 92% of Indian knowledge workers already use AI, with 77% using it daily.

OpenAI opened two new offices in Bengaluru and Mumbai, also partnered with Tata Group to deploy 100MW of AI compute under the HyperVault brand, scaling to 1GW. OpenAI is the first anchor tenant of TCS’s new data centre business. Altman confirmed 100 million weekly active ChatGPT users in India, second only to the US, and called India a potential “full-stack AI leader.”

Anthropic opened its first India office in Bengaluru and partnered with Infosys to deploy Claude into Indian enterprises, starting with a telecom Centre of Excellence. Cognizant is rolling Claude Code to 350,000 employees globally. Air India is using it to build custom software. Dario Amodei confirmed India is Claude’s second-largest market and noted that the “technical intensity of usage here is even more extreme” than elsewhere.

Nvidia expanded partnerships with Indian venture capital firms to deepen exposure to the startup ecosystem. Larsen & Toubro separately unveiled a gigawatt-scale AI factory built on Nvidia GPU infrastructure across Chennai and Mumbai. AMD and TCS are building rack-scale AI infrastructure on AMD’s Helios platform.

One geopolitical detail that deserves more attention: the US and India signed the Pax Silica agreement at the summit, a Trump administration initiative to secure the global supply chain for silicon-based technologies. India has also approved $18 billion in chip manufacturing projects. Compute sovereignty is being treated as a national security matter, not just an infrastructure one.

None of this is coincidental timing. India now sits in the top two markets for both OpenAI and Anthropic. Without being home turf for either.

What the Government Is Building

The corporate announcements got the headlines. The IndiaAI Mission story is the more durable one.

India’s national compute base of 38,000 GPUs is being expanded by a further 20,000 in the near term. The tech minister set a target of $200 billion in AI infrastructure investment over two years. The government-backed BharatGen consortium released Param 2, a 17-billion-parameter model covering 22 Indian languages, built for governance and citizen-service use cases.

One of the most significant knowledge outputs from the week was the release of the AI Impact Casebooks. Developed in collaboration with global partners like the WHO, IEA, and UN Women, these six thematic compendiums document over 170 real-world, scalable AI deployments across Healthcare, Energy, Agriculture, Education, Gender Empowerment, and Accessibility. Rather than focusing on theoretical pilots, these casebooks serve as a “Global South Playbook,” offering a first-of-its-kind consolidated repository for policymakers to replicate proven models, such as AI-driven crop planning and early disease diagnosis in their own regions.

India is not just building for itself. That is new.

Alongside these, the AI Impact Startup Book was launched to map India’s deep-tech ecosystem, highlighting that nearly 70% of India’s growth-stage AI ventures are already operating internationally.

The Domestic Model Stack

One thread that got less coverage than it deserved: India is building its own model layer, not just deploying someone else’s.

Sarvam AI released Sarvam 30B and Sarvam 105B, open-source, mixture-of-experts models built for Indian languages, alongside a full speech stack and Sarvam Kaze, smart glasses with on-device speech and vision. The underlying architecture is the point: intelligence that doesn’t require cloud connectivity, designed for the 800 million people at the edge of India’s network.

Cohere Labs launched multilingual open-weight models supporting 70+ languages, runnable on local devices. Gnani released Vachana, a zero-shot voice-cloning model across 12 languages. Cartesia partnered with Blue Machines on enterprise voice with local data residency. A distinct stack is forming, open-weight models tuned for Indian languages, speech infrastructure for multilingual contact, edge-first deployment for a population where the smartphone is the primary compute device.

This is not a replica of what OpenAI or Anthropic are building. It is a complement. And potentially an export product for Asia and Africa.

The Structural Advantage

India is not trying to outspend the US. Nor replicate China’s state-led model. Its advantage runs differently.

Aadhaar. UPI. ONDC. These are not pilots. They are population-scale systems, proven across linguistic, economic, and connectivity diversity. AI layered on top changes the arithmetic. For Instance, ONDC (Open Network for Digital Commerce), is the “final frontier” of India’s Digital Public Infrastructure (DPI). If Aadhaar solved for Identity and UPI solved for Payments, ONDC is solving for Market Access.

Fifty million pending court cases. Adalat AI launched a WhatsApp helpline this week, instant case updates and legal translation in native languages, built on Claude. AI-powered weather forecasts reached millions of Indian farmers last year through a Google DeepMind collaboration with the government. These are structural problems meeting capable tools at the right moment.

My Point of View

I grew up in India. I now lead global technology transformation programmes. This week’s summit signals land differently when you hold both perspectives.

India built its IT leadership on services excellence, reliable delivery, cost advantage, process discipline. That model is under direct pressure from agentic AI, and the people in this sector know it. CEO’s of large Indian IT firms may focus on profitability rather than job creation, in a way reflecting what is already happening to the $280 billion IT services industry.

The counter-signal is the startup layer. Emergent, an Indian vibe-coding platform announced $100 million in ARR and a new mobile app this week. That pace of scale, from a country where Anthropic had a single employee eighteen months ago, is the real signal about what the next generation of Indian technology companies looks like.

If India limits itself to fine-tuning global models cheaply, it remains a participant. If it builds sector-specific AI systems, invests in public datasets, and scales AI-native enterprises, it becomes an architect.

The intent is visible. The hard part starts now.

The Governance Shift Worth Watching

Bletchley was about safety. Seoul built on it. Paris tilted toward action. India reframed the whole conversation around impact, accessible, multilingual, public-good AI rather than frontier-lab debates.

A Leaders’ Declaration with 70+ signatories is being finalised. The UK-India bilateral AI showcase ran alongside, reinforcing cooperation on standards and commercialisation. The Pax Silica agreement with the US on silicon supply chains signals that AI governance and trade policy are now the same conversation.

For countries across Asia and Africa that have been observers in the Bletchley-to-Paris sequence, India is offering a different frame and a different set of partners. Whether that translates into durable architecture, or remains a positioning story, is the test over the next few years.

My Takeaway This Weekend

The India AI Impact Summit was not about demos.

The commitments are large and layered. $700 billion in global hyperscaler capex this year. $210 billion from Reliance and Adani alone. $200 billion in infrastructure investment targeted over two years by the government. Sovereign GPU capacity being expanded. Domestic foundation models in 22 languages. Global AI companies choosing India as their second home. A startup ecosystem generating nine-figure ARR.

For global technology leaders, one reframe is overdue. India does not belong in the AI strategy slide under “cost optimisation.” It belongs under innovation, deployment, and market creation. The question is no longer whether India is serious. It is whether your strategy is.

Weekend Notebook #2604 – Davos 2026 Highlights

amitabh apte
WEF Annual Meeting 2026 in Davos-Klosters, Switzerland, 19 January. Copyright: World Economic Forum/CHeeney

Published on LinkedIn and amitabhapte.com on25th Jan 2026

Every January, the world gathers in a Swiss ski resort to talk about the future. Often, that conversation lags reality by a few quarters.

Davos 2026 felt different. Two years ago, AI discussions revolved around existential risk. Last year, they fixated on generative possibility. This year, the mood shifted again. From magic to margins. From installation to deployment.

AI is no longer a side conversation at the World Economic Forum. It has become the organising logic for growth, energy, work, and geopolitics. And deployment, as every operator knows, is where things get complicated.

1. From demos to P&L

One of the clearest signals from Davos was how explicitly executives talked about money. OpenAI and Anthropic both framed 2026 as the year enterprise AI moves decisively into the core. OpenAI disclosed that the company is shifting from building AI tools to embedding them into how businesses actually run.

The conversation moved away from model benchmarks and toward return on invested capital. Financial services leaders pointed to underwriting and fraud detection. Manufacturers to predictive maintenance and yield optimisation. Healthcare executives to clinical workflow automation.

The implicit agreement was striking. AI has crossed the credibility threshold. The open question now is not whether it works, but where it delivers measurable payback, and how fast.

2. The capex reality check

This shift to P&L thinking exposed a deeper anxiety. AI deployment is proving capital-intensive at a scale few anticipated. Hyper-scalers are collectively spending hundreds of billions annually on data centres, chips, and networks. That spending was once absorbed comfortably by cash flows. At Davos, it was clear that boards are now scrutinising the economics more closely.

This wasn’t panic. It was operator realism. The question surfacing in private meetings was simple. Is this a temporary digestion phase, or the price of admission for the next decade of computing? The answer remains unresolved. What is clear is that deployment discipline is replacing experimentation exuberance.

This is the hangover phase. The technology works. Now, it must show it’s sustainable over a period.

3. The AI–energy equation moves centre stage

Nowhere was this more evident than in discussions on energy. Satya Nadella said energy costs will decide who wins the AI race. Access to cheap, clean, reliable power is becoming a strategic moat, not a sustainability footnote.

Sam Altman made similar observations on how AI’s progress depends on energy evolution. At Davos 2024, sustaining AI’s trajectory, he argued, ultimately depends on an energy breakthrough. Fusion, advanced nuclear, or radically cheaper renewables. Without it, the economics strain.

This reframed AI strategy entirely. Models and chips matter, but grids, land, cooling, and long-term power contracts now sit on the critical path. AI leadership has quietly become energy leadership. And that changes who wins.

4. From chatbots to agents, and beyond screens

On the product side, Davos revealed a growing impatience with the text box. After three years of marvelling that machines can converse, the demand is shifting to action. Agentic systems that can execute tasks across interfaces, applications, and environments.

Yet, the tone in Davos was notably pragmatic. Leaders acknowledged that this transition is less about model intelligence and more about unglamorous integration. APIs, standards, permissions, and human oversight. It feels less like a breakthrough moment and more like the web in the late 1990s. Everyone senses the inflection. No one has agreed on the standards yet.

At the same time, attention moved beyond screens to physical AI – robotics, automation, and autonomous systems are leaving labs and entering factories, warehouses, and cities. The emphasis was not spectacle, but supervision. Human-in-the-loop design and safe deployment dominated the discussion.

Intelligence is moving into the physical world. That raises the bar for trust.

5. Sovereign AI and the diffusion divide

Davos 2026 also made clear that AI is now a geopolitical asset. Panels framed AI as the next arena of statecraft. Less about ideology, more about who controls infrastructure, who captures economic upside, and who bears systemic risk.

The International Monetary Fund offered a sober warning. AI can lift global growth, but its infrastructure-heavy nature risks widening the gap between AI “haves” and “have-nots.” Unlike the internet, AI does not diffuse cheaply. Compute, energy, and talent concentrate advantage.

The implication for global business is significant, and unavoidable. We are moving from a world of open digital platforms to one of strategic national assets. AI infrastructure will be financed, regulated, and defended differently. And it will shape trade, alliances, and compliance for years to come.

6. Jobs, skills, and a fragile social contract

The jobs narrative matured as well. The tone shifted from “AI will kill jobs” to “AI will reshape future of work.” CEOs were notably candid, admitting that AI may sometimes be used to justify restructuring that was already inevitable.

What dominated instead was concern about transition. Reskilling at scale. Education systems that lag technological change. Policy experiments, including proposals to tax AI-driven productivity gains to fund workforce adaptation.

The consensus was not complacent optimism, but pragmatic urgency. The risk is not automation itself. It is unmanaged disruption.

7. AI as economic infrastructure

Perhaps the most telling Davos signal was how leaders described AI itself.

Demis Hassabis suggested the pathway to AGI is becoming clearer, sharpening the focus on safety and governance.

Jensen Huang described AI as foundational economic infrastructure, with impact determined not by who builds the smartest models, but by how widely intelligence is deployed across industries and regions.

This framing matters. Infrastructure is financed differently. Regulated differently. And built to last.

AI is no longer a feature. It is becoming part of the economic base layer.

My takeaway this weekend

Davos 2026 marked a turning point.

The magic trick has been performed. AI works. Now comes the harder phase. Building business models, power systems, skills pipelines, and governance frameworks that can sustain it.

The technical challenge is largely solved. The leadership challenge has only just begun.

The winners in this next phase will not be those who move fastest in isolation, but those who can integrate intelligence into economies and societies without eroding trust.

Davos wasn’t asking whether AI will shape the future. It was asking whether we are ready to live with the version of the future it is now shaping.

Weekend Notebook #48 – When AI gains momentum across global geographies

amitabh apte

Published on LinkedIn and amitabhapte.com on 30th Nov 2025

This week in AI – Growth beyond the West Coast, global players join the AI race

Some weeks, the AI narrative feels local, shaped by a handful of companies on the US West Coast.

This was Not one of those weeks.

This was the week AI revealed its global ambitions.
Not through model releases, but through cranes, concrete, capital, and policy.
Every region moved in its own direction, and for the first time, those directions felt equally significant.

Asia moved with industrial intent.

India’s Adani Group is reportedly in talks with Google on a multi-billion-dollar data-centre partnership. India is no longer content being the world’s digital back office. It wants to be a compute power in its own right.

Japan, meanwhile, approved Micron’s $96B semiconductor project, not a press release, but a generational bet on the Indo-Pacific becoming the world’s memory and materials corridor.

China took a different route.

Alibaba didn’t just talk about AI; it shipped it, Quark AI glasses and a cloud business now lifted by real workloads. China may not be leading the frontier-model race, but it is winning the deployment race. Intelligence at the edge, not just the cloud.

Africa showed the geopolitics beneath the ambition.
A WSJ investigation revealed Chinese firms now control nearly half of Africa’s IPv4 addresses. This is not an obscure technical footnote. In an AI-driven world, whoever controls the pipes controls the possibilities.

Europe leaned into its slow. steady. deliberate. advantage.

A new CNBC analysis suggests Europe’s measured approach may age better than Silicon Valley’s “move fast” doctrine. Markets seem to agree, Germany’s stock market is climbing again. Siemens Energy is emerging as one of Europe’s biggest beneficiaries of the AI-driven infrastructure boom with nearly a 100B Euro valuation.

The UK added its own twist: Qatar invested hundreds of millions into a British quantum startup, strengthening Britain’s emerging position in the quantum race.

And Revolut’s new $75B valuation underscores something deeper: global finance is quietly becoming one of AI’s most powerful accelerators, built on software, data, and automated risk intelligence.

The Middle East kept doing what it always does. Skip the pilot. Go straight to scale.

Uber’s driverless robotaxis will now operate commercially in the UAE. Not a test. A rollout. AI is becoming lived infrastructure faster than many Western cities can regulate it.

Zoom out, and one conclusion becomes impossible to ignore.

“AI is no longer a Western invention. It is a global construction project.”

My takeaway this weekend

AI is no longer a single race.
It’s a set of parallel movements shaped by regional ambition.

India and Japan are building the physical backbone. China is pushing intelligence into daily life. Europe is turning trust into strategy. The Middle East is deploying at city scale. Africa is emerging as the new arena for digital sovereignty. And the UK is betting on quantum, the foundational layer beneath it all.

The real question has shifted. Not “Who has the smartest model?”, but “Who can build the steadiest system around it?”

Compute, energy, policy, capital, trust this is where advantage now compounds.

AI leadership is moving from algorithms to infrastructure.
From speed to readiness.
From capability to resilience.

“The next winners won’t be the fastest movers. They’ll be the regions and leaders who can scale AI meaningfully across diverse geographies and real consumer impact.”

Beyond AI: my mindshare – the comfort of Christmas Films

This post comes just a day before December. Is it too early to think about Christmas? Perhaps. But there’s something timeless about the way certain films weave themselves into our holiday rituals.

This week, The Times published a beautiful guide to the best Christmas movies to stream, a reminder that stories can be as comforting as a warm blanket on a cold evening.

From the mischief of Elf and the tangled romances of Love Actually to the quiet grace of It’s a Wonderful Life, these films aren’t just entertainment. They are memory-makers. They carry the scent of mulled wine, the glow of fairy lights, and the soft permission to slow down.

What struck me most is how these classics endure despite infinite choice.

In a world of endless scrolling, we still return to the familiar to Bedford Falls, to Kevin McCallister’s misadventures, to the belief that hope can arrive in the most unexpected ways.“Perhaps that’s the real gift of the season: the chance to pause, revisit old stories, and let them remind us of what matte

Weekend Notebook #42 – Lights of Progress: from Smart Glasses to Smart Economies

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Published on LinkedIn and AmitabhApte.com on 19th Oct, 2025

This week in AI – When AI Becomes Tangible

This week, AI stepped further out of the cloud and into the real world, shaping markets, moving currencies, and rewriting the geography of innovation.

EssilorLuxottica’s record-breaking quarter sent its shares up nearly 14% to an all-time high. The driver? Its AI-powered Ray-Ban Meta smart glasses. Once a novelty, they now represent a powerful convergence of hardware, intelligence, and design. The blend of form, function, and data is transforming wearables from accessories into interfaces, subtle, seamless, and socially acceptable. When design meets purpose, adoption accelerates.

Meanwhile, OpenAI’s new partnership with Broadcom marks a decisive move from software to silicon. By co-designing custom AI chips, OpenAI aims to reduce dependence on Nvidia and secure its own compute future. This is the next wave of integration, from algorithms to architecture, from models to metal, giving OpenAI control over both intelligence and infrastructure.

Finance, too, is recalibrating around AI’s physical footprint. Goldman Sachs is building a new lending unit to finance AI infrastructure, while BlackRock’s $20 billion acquisition of Aligned Data Centers ranks among the largest in the sector’s history. Infrastructure is now investable; data centres, cooling systems, and energy grids are becoming the new ports and pipelines of the digital age.

The wave is global, and India is fast becoming one of its most ambitious players. Google’s $15 billion investment in a new AI data centre in Visakhapatnam, , underscores India’s “swadeshi tech” ambition to localise AI infrastructure. To power this growth sustainably, the country is also exploring small modular nuclear reactors (SMRs) for round-the-clock clean energy, a bold shift from renewables that opens its nuclear sector to private and foreign investment.

Beyond India, the ripple effects are being felt across economies. Sterling and the Swedish krona are both strengthening as capital flows into new AI data hubs in London and Stockholm. Analysts call it the “compute capital effect”: when technology investment starts to influence currency strength and macro stability. Innovation, in other words, is becoming an economic moat.

And as AI enters new domains, society is adapting in parallel. Instagram’s upcoming parental controls for AI chatbots show how platforms are finally acknowledging their responsibility for young users’ wellbeing. In healthcare, AI is reducing administrative load and clinician burnout, yet only 28% of doctors feel ready to use it effectively. The technology is advancing faster than human capability to absorb it. That readiness gap is emerging as one of the defining leadership challenges of our time.

My Takeaway This Weekend

From eyewear to energy, from silicon to society, one theme connects it all: AI is crossing from the digital layer into the physical economy. It’s no longer something we log into; it’s something we live within.

“This is the industrialisation of intelligence, when data becomes infrastructure, and infrastructure becomes intelligent.”

For leaders, the task ahead is to design for that convergence, where compute, capital, and culture intersect. Because the next decade of AI won’t just be coded in labs; it will be built in factories, financed by markets, powered by clean energy, and worn on faces.

Beyond AI: My mindshare – the Light we share

This week, as millions around the world celebrate Diwali, the festival of lights, homes, offices, and streets glow with lamps, laughter, and the scent of homemade delicacies.
It’s a time to pause, reconnect with family and friends, and celebrate the warmth of togetherness.

For me, Diwali has always been about more than lighting diyas. It’s also a reminder to light the lamp within, the spark of compassion, curiosity, and kindness that brightens the lives of those around us. Each flame we light carries meaning: to share joy, to help someone find their spark, and to bring others along on our journey.

In a world that often feels fast and fragmented, Diwali invites us to slow down and rekindle what truly connects us, gratitude, generosity, and shared light.

“When we light a lamp for someone else, we illuminate our own path too.”

Weekend Notebook #39 – When Capital Meets Compute

amitabh apte

Published on LinkedIn, Substack and AmitabhApte.com on Sept 28, 2025

In spotlight this week: The $100 Billion Question

Nvidia is planning to pour $100 billion into OpenAI to build next-generation data centres, in what could become the most ambitious AI infrastructure bet ever. On paper, it’s a marriage of two giants: Nvidia supplies the silicon, OpenAI drives demand. The ambition signals nothing less than the industrialisation of AI.

But there’s a tension here. Much of this capital will circle back to Nvidia’s own chips, fuelling whispers of “closed-loop” deals that echo dot-com era excess. Analysts are already asking: are we funding productivity revolutions, or inflating another bubble?

The stakes couldn’t be higher. If this bet delivers, we could see an acceleration of AI capability at a planetary scale. If it falters, the correction could be sharp, reshaping both capital markets and public trust.

Walmart’s CEO Doug McMillon added a sobering perspective: headcount will stay flat even as business grows, because AI will take on roles that once required people. Coming from the world’s largest private employer, this isn’t abstract, it’s the front edge of a workforce reset that will ripple far beyond retail.

My take: We’ve entered the era where compute has become capital. AI is no longer just software; its steel, energy, land, and labour economics. Leaders must prepare for the dual challenge: harnessing unprecedented opportunity while cushioning society from unprecedented disruption.

Noteworthy this week: what caught my eye in the AI and tech world

I track the week’s big currents across leadership, geopolitics, policy, infrastructure, and people. Three themes stood out this week:

1. Cybersecurity: breaches are now brand events

  • Harrods confirmed a breach via a third-party vendor; customer names and contact details compromised. Another reminder that supply-chain risk is now brand risk.
  • JLR is recovering from a major September cyberattack that halted production and shipments. Global supply chains remain brittle, and resilience is now as important as efficiency.

2. Infrastructure – capital meets fragility

  • Beyond Nvidia’s $100bn, OpenAI also struck a $400bn partnership with Oracle and SoftBank, and tied up with Databricks to deepen enterprise adoption. Lofty projections of $125bn revenue by 2029 and “trillions” in future data-centre spend highlight both ambition and fragility.
  • Anthropic is tripling its workforce and expanding globally, with 80% of usage now outside the US. From pharma to finance to governments, we’re moving from AI pilots to enterprise-scale deployments. The AI arms race is now unmistakably global.

3. Policy & People – platforms redraw the line

  • Spotify removed 75 million low-quality AI-generated tracks. Platforms are drawing new lines between innovation and integrity. Protecting human creativity is now a business necessity.
  • Neon, an app that pays users to record calls for AI training, has triggered major privacy alarms. The trade-off between data, consent, and profit is becoming the next trust battleground.
  • Global talent shifts: Indian Global Capability Centres are no longer just back-offices; they’re producing CXOs for Tesco, Walmart, SAP, and Maersk. By 2030, an estimated 30,000 global leaders will emerge from this pipeline, a structural rebalancing of corporate power.

Beyond Tech & AI: my “mind share” this week

This week I tuned into Steven Bartlett’s Diary of a CEO podcast with Dr Pradip Jamnadas, a cardiologist known as “the fasting doctor.” is insights were striking: modern diets overload us with insulin spikes, while simple practices like intermittent fasting and better sleep can transform long-term health.

It’s a timely reminder that while AI scales our external capability, it’s disciplined self-care that sustains our inner resilience.

In summary: my key takeaway this weekend

“Capital is racing into compute. Leadership must race just as hard to scale responsibility“

Weekend Notebook #38 – Building AI nations, not just AI models

amitabh apte

Published on LinkedIn, Substack and AmitabhApte.com on Sept 21, 2025

In spotlight this week: UK’s $200B AI Moonshot


President Trump’s UK visit culminated in a Tech Prosperity Deal with Prime Minister Keir Starmer, announcing over $200 billion in US–UK tech and AI investment. Microsoft pledged $30B over four years to expand AI and cloud infrastructure, Google committed $5B to boost AI and data centre capacity, and Nvidia invested £500M in Nscale as part of a broader £11B push into UK-based AI factories powering projects like OpenAI’s Stargate and Microsoft’s new supercomputer.


This deal signals a decisive shift: the UK is not just regulating AI, it is building itself into a sovereign AI hub. Tens of thousands of jobs will be created, supply chains for GPUs and compute will be strengthened, and Britain’s role in transatlantic AI collaboration will deepen. In an era where compute is the new oil, data centres and sovereign infrastructure are the new battlegrounds for economic and geopolitical advantage.


My PoV – This is the UK’s moonshot moment. Infrastructure at this scale could anchor Britain as a global AI leader, but steel and silicon alone aren’t enough. The real test is whether investment translates into skills, trust, and adoption that benefit society as well as industry. For business leaders, the takeaway is clear: the future of AI competitiveness isn’t about building smarter models, it’s about building the foundations that let those models thrive.

Noteworthy this week: what caught my eye in the AI and tech world

Talent, regulation & geopolitics

  • The U.S. has escalated its H-1B visa crackdown, imposing a $100,000 fee that is forcing Indian IT firms to curb onshore rotations and accelerate offshore models. Tech giants like Microsoft, Amazon, Meta, and JPMorgan are warning foreign employees not to travel, underscoring how policy shifts directly reshape global talent flows.
  • TikTok has won a reprieve in America under a new deal that reduces Chinese ownership below 20% and places Oracle in charge of U.S. data, a blueprint for how national security concerns could reshape tech governance going forward.

Consumer trust under pressure

  • The Amazon Prime trial will test whether subscription giants have been deliberately making cancellations too complex. If the FTC prevails, Amazon could be forced to simplify flows, setting new norms for consumer rights in digital services.
  • Across the Atlantic, a cyberattack on European air travel systems grounded flights at Heathrow, Berlin, and Brussels, shaking public trust in critical infrastructure and spotlighting how fragile digital-first services remain in the face of cyber risk.

The infrastructure arms race

Hardware sovereignty & intelligence on the edge

  • Apple is accelerating its in-house chip strategy, prioritising AI-optimised silicon that boosts on-device intelligence, efficiency, and privacy while reducing reliance on third parties. Taken with Nvidia and Oracle’s bets, the story is clear: hardware design and infrastructure control are becoming the new frontiers for competitive differentiation in AI.

Beyond Tech & AI: my “mind share” this week

Being back at Barilla’s Parma HQ in the heart of Italy’s Food Valley was both inspiring and grounding. While plenty of Data, Tech and AI conversations kept me busy, what made the week truly special was the chance to sit with colleagues across cyber, data, infrastructure, and sales. Listening, learning, and aligning on our shared priorities. Moments like these remind me that while AI, digital, and data drive transformation, the culture, humility, and human connection that give those technologies meaning and staying power.

In summary: my key takeaway this weekend

“From moonshots in London to conversations in Parma, the same truth echoed: AI’s future won’t be written only in code or capital. It will be written in the bridges we build between technology and trust, scale and society, steel and soul.”

Weekend Notebook #34 – From Cloud to Chip- The AI Assistant Revolution

amitabh apte

Published on LinkedIn, Substack and AmitabhApte.com on August 24, 2025

In spotlight this week: AI assistants go mainstream – Apple eyes Gemini, Google embeds it.

What if your phone didn’t just respond to you, but anticipated your needs before you spoke? This week, AI assistants took a giant leap from cloud-based helpers to embedded, proactive companions. Apple is reportedly in talks with Google to integrate Gemini into Siri, potentially transforming its underwhelming assistant into a multimodal powerhouse. While no deal is confirmed, the move signals Apple’s openness to external AI partnerships, including ongoing discussions with OpenAI and Anthropic. The goal: to bring richer, more conversational intelligence to iPhones and across Apple’s ecosystem.

Meanwhile, Google has taken a decisive leap forward with the launch of its Pixel 10 smartphone lineup, embedding Gemini AI directly into the device via its new Tensor G5 chip. The Pixel 10 series introduces features like Magic Cue, which proactively surfaces relevant info across apps, and Gemini Live, which offers real-time visual assistance based on what the phone sees. Other AI-powered upgrades include Voice Translate for multilingual calls, NotebookLM integration for smarter notetaking, and Pixel Journal for wellbeing tracking. The Pixel 10 Pro models even come bundled with a year of Google AI Pro subscription, unlocking creative tools like Imagen 4 and Veo 3.

My key takeaway: The battleground is no longer just software. It’s the device, the chip, and the ecosystem. Apple is pivoting strategically, Google is executing decisively. Both point to the same future: assistants that are native, multimodal, and deeply personal.

Noteworthy this week: what caught my eye in the AI and tech world

Meta + Midjourney – Meta has struck a deal to license Midjourney’s image-generation tech for future products. It’s a boost in visual creativity and a possible hedge against the lukewarm response to its own Llama 4. Partnerships like this are signals. Meta knows it needs an edge beyond its own labs.

Intel agrees 10% U.S. stake –Intel is selling a 10% stake to the U.S. government, one of the largest federal equity moves since the 2008 auto bailout. It strengthens chip sovereignty but also raises a hard question: what happens when governments become shareholders in the engines of tomorrow?

New turn in Nvidia’s chip for China – Nvidia has stopped producing its H20 chip for China after Beijing told local firms not to buy it, despite U.S. approval. It’s the latest flashpoint in the U.S.–China tech standoff. Critical AI infrastructure is seen as differentiator in increasing tense geo-political scenarios.

Coinbase firing engineers for not onboarding AI – Engineers who failed to adopt tools like GitHub Copilot were let go. Coinbase calls it “AI fluency or out.” Yes, fluency in AI is now non-negotiable. But enforced adoption without empathy risks losing talent and trust.

TCS opens AI-led operations centre in LATAM – A new AI-led operations centre marks its eighth in the region. Jobs, skills, and digital transformation are the pitch. Indian IT giants are exporting AI at scale, and LATAM is the next growth frontier.

TikTok to replace UK staff with AI –Over 85% of moderation is now automated, with thousands of roles at risk. Efficiency is up but user trust may not be. Platforms can’t trade human oversight for pure automation without ethical safeguards.

In summary: my key takeaway this weekend

This week marks a turning point. AI assistants are no longer cloud novelties, they’re becoming embedded essentials. Apple is courting Gemini. Google is hard-wiring it into Pixel 10. Meta, Intel, Nvidia, Coinbase, TikTok, each move adds to the same message: AI isn’t just a feature. It’s the new operating system of everything. The question now is not if you’ll use an assistant, but whose ecosystem you’ll live in.