AI/ML News & Innovations Hub

😺 Apple's brain drain continues 🍎

PLUS: AI is killing entry-level jobs, and Google ran out of compute for Meta.

Robotics has a data problem. Macrodata Labs wants to solve it

The AI industry has spent the past several years learning a critical lesson: better data often matters as much as better models. While advances in large language models have been powered by increasing...

Fireworks Are Not Patriotic. Drone Shows Are

This Fourth of July will feature more drone shows than ever. I went on a pilgrimage to drone country—and had a near-religious experience.

Top Google Security Staff Warn Search Data Could Be Hacked if EU Rules Change

Europe’s pro-competition proposals could see Google Search and Android systems opened up. The company claims there are serious privacy flaws.

Everyone’s Mad at the World Cup’s New ‘Hydration Breaks’—Except Mr. Moneybags Over Here

FIFA says hydration breaks protect players from heat. They also create new annoying commercial breaks—and fans are calling foul.

Beyond automation: How much does AI really cost?

The problem nobody budgeted for An anonymous enterprise recently spent $500 million in a single month on Claude AI — not because the technology failed, but because nobody set usage limits before rolling it out to employees. Uber exhausted its entire AI budget for 2026 before the first half of the year ended . JPMorgan published a report titled “ AI Token Costs Are Eating into Internet Profits .” Shopify, Spotify, ServiceNow and Roku all cited AI as a major source of operational expense pressure in recent earnings calls . This is not a technology problem. It is a cost modelling problem. Most organizations ask the right first questions: What work should be AI-enabled? Which deployment approach fits each domain? But there is a third question that is almost never asked before launch: How much will it cost to operate this at scale? The answer requires understanding three parameters simultaneously — and the interaction between them is deeply counterintuitive. The deployments that did not produce budget surprises shared one characteristic: token volume was modelled per workflow type before the architecture was finalized. The 3-parameter cost model AI operational cost is not simply a function of how complex or sophisticated the task is. It is the product of three variables: Total AI Cost = Tokens (activity) × Frequency (repetitions) × N (users) Tokens(activity) measures the cognitive depth of a single session — how much input and output the AI processes to complete one instance of t…

Absa’s giant steps to rebuild its integration foundation

With headquarters in Johannesburg, South Africa, Absa also operates in many other African countries, with international offices in Europe and the US. Running an organization across several markets has its unique complexities, especially in the integration layer, because each region has its own systems, business processes, regulatory requirements and data standards. For Absa, replacing an integration layer that had reached breaking point was a fundamental shift in its banking philosophy. It wasn’t just a technical project. Duplication was rampant, complexity was baked in, and reusability was non-existent. Every change had far-reaching ripple effects, and each new channel had to be built from scratch. As it stood, making the improvements the business demanded at the speed required to remain competitive was impossible. According to Tamu Dutuma, Absa’s head of technology strategy for Africa Regions, this integration layer had been in place for close to a decade. While it played an important role in enabling business in the past, it was too difficult to maintain and no longer aligned to current standards and ways of working. Integration standardization Absa evaluated a range of available solutions in the market, but given the complexity of integrating with legacy systems across a multi-country financial environment, the team decided a more tailored approach was required. “It was critical to establish the right architecture from the outset, which is why we worked with a strategic…

End of era as the BBC switches off Radio 4 Long Wave service

Aging infrastructure shuts down tomorrow after almost a century

The Capitalist Ventures bags Rs 10 Cr seed round

The Capitalist Ventures, a Hyderabad-based entrepreneurial venture company operating at the intersection of private luxury concierge and culture-driven commerce, has raised Rs 10 crore in a seed funding round from M Sriram and other angel investors. The fresh funds will be utilized to expand luxury product portfolio, accelerate customer acquisition and brand-building initiatives, and strengthen operational infrastructure, The Capitalist Ventures said in a press release. Launched in 2025 by Satyaram Nadimpalli, The Capitalist Ventures is focused on building trust-led ecosystems centered around access, exclusivity, and high-value opportunities. Its two core verticals, The Plug and The Capitalist Concierge, serve India’s evolving premium consumer market, offering access to rare sneakers, streetwear, luxury assets, collectibles, and private deal flow. The Capitalist Ventures operates two distinct verticals, The Plug, a community-driven sneaker and streetwear platform, and The Capitalist Concierge, a private luxury concierge service catering to HNIs and UHNIs seeking access to exclusive collectibles. Together, the verticals position the company as a full-stack access infrastructure for India's growing new-wealth class. The company plans to accelerate market presence, with growing demand for authenticated luxury products and exclusive sourcing, it says that the company is well-positioned to scale both in India and across global luxury hubs including Dubai, Milan and Spain.

클로드 코드 총괄 “프로토타이퍼·빌더·그로워…AI 시대 조직은 이렇게 바뀐다”

앤트로픽에서 AI 코딩 도구 클로드 코드 개발을 주도하고 관련 팀을 총괄하는 보리스 체르니 (Boris Cherny)는 28일 X를 통해 내부 제품 조직을 관찰한 결과를 바탕으로 미래 제품 조직의 다섯 가지 핵심 역할을 제시했다. 첫 번째는 ‘프로토타이퍼(Prototyper)’다. 새로운 아이디어를 끊임없이 발굴하고 빠르게 실험하는 역할이다. 수많은 아이디어를 만들어내지만 실제 제품으로 이어지는 것은 일부에 그친다. 두 번째는 ‘빌더(Builder)’다. 프로토타입이나 아이디어를 빠르게 실제 서비스 수준의 제품과 인프라로 구현하는 역할이다. 세 번째는 ‘스위퍼(Sweeper)’다. 사용자 인터페이스(UI)를 다듬고 코드와 시스템을 단순화하며, 불필요한 기능을 제거하고 성능을 최적화하는 역할을 맡는다. 네 번째는 ‘그로워(Grower)’다. 이미 출시된 제품을 지속적으로 개선하며 제품-시장 적합성(PMF·Product-Market Fit)을 높이는 데 집중한다. 마지막은 ‘메인터이너(Maintainer)’다. 성숙한 시스템의 보안성과 안정성, 성능, 운영 효율성을 유지하고 서비스 확장을 책임지는 역할이다. 체르니는 “많은 사람은 이 가운데 두 가지 역할을 수행하고, 때로는 세 가지 역할까지 아우른다”며 “흥미로운 점은 이러한 역할이 기존 직무와는 크게 관련이 없다는 것”이라고 설명했다. 그는 “앤트로픽에서도 디자이너 가운데는 프로토타이퍼에 가까운 사람이 있는가 하면, 빌더나 스위퍼 역할을 수행하는 사람도 있다”며 “엔지니어, PM, 데이터 사이언티스트 역시 마찬가지”라고 덧붙였다. 또한 체르니는 건강한 제품 조직은 제품의 성장 단계에 따라 필요한 역할의 조합이 달라진다고 설명했다. 초기 제품에는 새로운 아이디어를 만들고 이를 빠르게 구현·정리하는 역할이 중요하다. 제품이 성장하기 시작하면 이를 지속적으로 개선해 PMF를 높이는 역할과 시스템 안정성을 유지하는 역할이 추가된다. PMF를 확보한 성숙한 제품에서는 안정성과 성능 개선, 지속적인 제품 고도화가 핵심이 되며, 새로운 기능 개발을 담당하는 역할은 일부만 필요하다는 설명이다. 체르니는 “어쩌면 미래의 제품 조직은 지금처럼 엔지니어, 디자이너, PM 등 직무별로 구분되기보다 이러한 역할(archetype) 중심으로 구성되는 형태에 더 가까워질지도 모른다”고 밝혔다. 몇몇 IT 업계 리더들도 비슷한 전망을 내놓은 바 있다. 마이크로소프트(MS) CEO 사티아 나델라는 AI 시대에는 업무 방식뿐 아니라 직무의 범위 자체가 재편되고 있다고 진단했다. 나델라는 2025년 공개된 와이콤비네이터(Y Combinator)와의 대담 에서 MS가 보유한 링크드인을 사례로 들며 “링크드인은 기존에 별도로 운영되던 제품 디자인, 프런트엔드 엔지니어링, 제품 관리(PM) 기능을 하나의 역할인 ‘풀스택 빌더(Full-stack Builder)’로 통합하기 시작했다”고 설명했다. 그는 “이는 직무의 범위 자체가 달라지고 있다는 의미”라며 “새로운 역할과 직무 범위에 맞춰 제품팀을 어떻게 다시 설계할 것인지가…

Event report: Age Verification and Restricting Social Media for Children, Bengaluru, 15 May #NAMA

MediaNama's roundtable explores whether India's proposed age verification framework can balance child safety, privacy, and internet access. The post Event report: Age Verification and Restricting Social Media for Children, Bengaluru, 15 May #NAMA appeared first on MEDIANAMA .

A Statistical Question Concerning the Birthday Problem

We know that, under the simplifying assumptions that a year has 365 days (i.e., ignoring leap years) and that each day is equally likely to be a person's birthday, the probability that at least two people in a group of $n$ share the same birthday is $$ 1-\frac{365}{365}\cdot\frac{364}{365}\cdot\frac{363}{365}\cdots\frac{365-(n-1)}{365}. $$ This probability increases nonlinearly with $n$ . For example, it exceeds $50$ % when $n=23$ , is about $81$ % when $n=35$ , and about $99.4$ % when $n=60$ . I have conducted this experiment on at least four different occasions, each involving around 30 participants. Every time, there was at least one pair of people sharing the same birthday. This makes me wonder whether the assumption that birthdays are uniformly distributed over the 365 days is realistic. More generally, how can one formally test/assess the validity of the equal-likelihood assumption based on repeated observations of birthday matches? PS: I do not have a formal background in statistics. (I have a math background) So, any rigorous explanation concerning solution of this question is greatly appreciated.

I oversee all courts at Wimbledon. A typical workday during the Championships is 15 hours long and fueled by adrenaline.

Wimbledon's head of courts and horticulture, Neil Stubley, shares a typical daily routine during the tennis championships.

An EY leader shares the smartest move she's seen a candidate make

Francesca Jones recalled a recent candidate who snuck into a career fair at a large university that he didn't attend.

Comment on NVIDIA’s Hybrid: Combining Attention and State Space Models for Breakthrough Performance of Small Language Models by apk

I like the direction of this article, though I think it could go deeper into real-world applications. The practical side is where most users struggle..

OpenAI's head of Codex says AI still can't get creative design right: 'Give it up for the human brain'

AI is revolutionizing all kinds of industries, but there are some things it still can't quite get right, and, by most accounts, design is one of them.

Top China chip toolmakers consolidate to build national champions, defy US curbs

China’s campaign for semiconductor self-sufficiency has entered a consolidation phase, with state-backed toolmakers swallowing smaller rivals in a bid to forge national champions aimed at defying US export curbs. In the latest move, Shanghai-listed chip equipment maker Piotech said in a filing to the stock exchange on Saturday that it planned to acquire a controlling stake in Wuxi Shangji Semiconductor. Piotech’s largest shareholder was China’s state-backed National Integrated Circuit Industry...

SmartPhilm Fest 2026 in Addis Ababa Explores AI’s Role in Storytelling Across 112 Films From Five Continents

In recent months, much of the conversation around creativity has centered on artificial intelligence. Will AI transform storytelling? Who owns the future of content creation? How do creators adapt to a rapidly changing media landscape? These are important questions. But after reviewing 112 films submitted to SmartPhilm Fest 2026 from filmmakers across five continents, another [...]

I'm a 38-year-old software engineer making $200K a year. I grew my salary by moving to the US and plan to retire soon in Mexico.

A 38-year-old who makes $200,000 living in California shares his salary journey over 18 years.

UK firm bombarded debt-ridden people with 5.5M texts

KRA Consultancy Ltd fined £300K over fake bailiff threats in 'calculated' scheme that caused 'real fear and distress'

In the AI age, clients are now asking consulting firms to have 'skin in the game'

Consulting giants like BCG and Accenture are shifting from fixed rates to outcome-based fees as clients push them to share the risk of AI integration.

Absa Kenya CEO Abdi Mohamed steps down after 32-year career

Abdi Mohamed, chief executive officer of Absa Bank Kenya, one of Kenya's tier 1 banks, will step down on June 30 after three years in the role and a 32-year career with the lender, ending one of the longest tenures by a senior banking executive in Kenya's banking sector.

American national pride recedes across parties, poll finds

One-third of US adults say they are “extremely proud” to be an American, according to Gallup.

Democrats’ ‘Project 2029’ goes after tech companies with online safety plan

The liberal counterweight to conservatives’ Project 2025 is rolling out a series of policies to set the stage for an already crowded field of 2028 presidential hopefuls.

We're childhood friends who scaled our startup to $13M by age 21. Dropping out of college was the right move — if anything, we did it too late.

Two childhood friends scaled an AI study app to $13 million in revenue and say using AI to code is powerful but comes at a cost.

New Hampshire becomes the Senate midterms’ sleeper race

Democrat Chris Pappas warns his party not to be “overconfident.”

How Spain has emerged as one of Europe’s most dynamic tech ecosystems

I'm 63 and raising 2 grandchildren alone. It's cost me my retirement years, but I wouldn't trade it for the world.

Rebecca Black, 63, has raised her grandsons since 2020. She left her job to care for them full-time, resulting in financial strain.

Nigeria’s fintechs built payments. Now they’re becoming banks.

An MFB licence allows fintechs to accept deposits, give loans, and earn interest income from lending, reducing their reliance on transaction fees.

Chinese AI model’s bug-hunting prowess narrows gap to US

A Chinese artificial-intelligence (AI) model whose launch has been hailed as another “DeepSeek moment” can go toe-to-toe with US rival Anthropic’s powerful Mythos model on cybersecurity tasks, researchers have said. Beijing-based start-up Zhipu AI’s GLM-5.2, released on June 13, beat Anthropic’s Claude Opus 4.8 model in benchmarking tests by cybersecurity company Semgrep, The Wall Street Journal reported. When Semgrep researchers gave it further instructions, GLM-5.2 matched that model and...

A self-sustaining private island in Canada sold for $6 million — it can only be reached by boat or helicopter

A luxurious lodge on a private island in Nova Scotia with enough infrastructure to maintain life off the mainland was sold for $6 million.

How to make Linux look like MacOS for free - with a few simple ZorinOS tweaks

Looking to migrate to Linux but fond of the Mac UI? Zorin OS can help make your new distro look very much like the one you just left. Here's how to achieve that for free.

When software developers and AI agents share the learning

Before Tobi Lütke ran Shopify, he learned programming through Germany’s apprenticeship system⁠, the way people have learned trades forever: in a shared workshop, watching people who already knew what they were doing. More recently, describing Shopify’s River , he reached for a related word: Lehrwerkstatt ⁠, a teaching workshop where “the whole shop floor is the classroom.” X has been agog by the numbers around River ⁠, Shopify’s Slack-native AI agent . In total, 5,938 Shopify employees worked with River across 4,450 different Slack channels, and River now coauthors roughly one in eight merged pull requests across the company. It’s a big deal, but understanding why it works that way is the most important part. River can read code, run tests, open pull requests, query the data warehouse, inspect production traces, and sometimes push back on a plan it thinks is bad. Great. Lots of companies will have clever coding agents someday soon. Some already do. The interesting part is that River doesn’t work alone; it works where everyone can see it. Betting on the workshop I’ve already argued that agents reward explicit, consistent, well-documented software . They like the “boring” stuff, such as schemas, tests, conventions, clean setup instructions, and codebases that don’t require a deep retrospective with the one engineer who remembers why the build script has to run twice. Dropping an agent into a messy repo is mostly an efficient audit of your engineering discipline. Agents hold up…

AI needs a flight school

In the late 1960s, elite Navy pilots began losing dogfights. The deep, instrument-level understanding of exactly where they were, what their aircraft was doing, and what was coming next had been automated. And when moments of crisis arrived, they didn’t have the situational awareness to respond. Put a plane on autopilot long enough, and the pilot stops actually flying. The same dynamic is playing out across enterprise software. AI is generating code faster than developers can understand it , and leaders are celebrating the velocity without asking who’s actually flying the plane. A developer who has only ever “vibe coded” has perception at best. They can “see” the outputs but can’t fix any internal failures caused by the very AI systems they’re relying on. The easiest thing to do is to say the answer looks good enough. Cut and paste it in and hope it works out. According to Model Evaluation & Threat Research’s randomized control trials , experienced developers working with AI tools actually took 19% longer to complete tasks than those working without them, despite predicting beforehand that AI would make them 24% faster. The fundamentals of good software delivery have never been more important — and never more neglected. When instruments go dark The Navy’s answer to training dogfighters for success was the Top Gun school — not just to teach pilots to fight, but to teach them how to fly again. That meant returning to the fundamentals by mastering the technical and combat skill…

Truckloads of Tesla Batteries Keep Getting Stolen Before They Even Leave the Factory

Nine major suspected cargo thefts happened at Tesla’s Nevada battery factory in January alone, according to sheriff’s records obtained by WIRED.

The rise of the product engineer: How AI is reshaping modern tech teams

The end of pure specialization For years, software organizations optimized around specialization. Product managers owned requirements. Engineers owned implementation. Designers owned UX. QA owned quality. The model worked – until product velocity became a competitive advantage measured in weeks instead of quarters. Today, AI is accelerating another shift that I believe will fundamentally reshape how high-performing technology teams operate: the rise of the product engineer. As Chief Technology Officer of akirolabs, an AI-augmented strategic procurement platform serving enterprise-scale clients, including Fortune 500 organizations, I’ve spent the last several years evolving our engineering model through three distinct stages. First, I dismantled highly specialized silos. Then I transitioned the organization toward more flexible generalists. Eventually, our operating model revealed that the teams performing best in the AI era were neither traditional specialists nor pure generalists, but engineers deeply embedded in product thinking and business context. I formalized and operationalized this role internally as a product engineer model, adapting an increasingly common industry pattern to enterprise AI delivery. This role does not replace product managers. Instead, this operating model elevates strong product managers by removing operational friction. In our organization, product managers became more focused on customers, roadmap prioritization, requirement validation and strate…

The great cloud rebalance

For years, the enterprise narrative focused on moving to the public cloud for flexibility and leaving behind old infrastructure. While the public cloud remains a powerful platform for burst capacity, global reach, and modern application development, leaders now evaluate where each workload can achieve the best financial performance, operational efficiency, and risk. Cloud repatriation is back on the CIO’s agenda. Cloud repatriation does not always mean dragging workloads back into a company-owned data center. In many cases, enterprises are moving applications and data from hyperscale public cloud platforms into colocation environments, hosted private clouds , or MSP-operated infrastructure. The common thread is not nostalgia for on-premises IT. It is the desire for a more suitable workload placement. Enterprises are deciding that some systems belong in public cloud while others are better served in environments with more predictable economics, tighter control, and fewer architectural compromises. Cost is the loudest signal The most common reason enterprises repatriate workloads is cost. Public cloud pricing works extremely well when demand is variable, when teams need rapid provisioning, or when a business wants to avoid upfront capital spending. But not every enterprise workload behaves that way. Many core systems are steady, always-on, data-intensive, and relatively predictable. For those workloads, usage-based pricing can become less attractive over time. Compute charges,…

Europe’s industrial wake-up call

Europe’s climate ambitions must integrate with industrial competitiveness. The upcoming EU ETS reform should support decarbonization while ensuring affordable energy, investment certainty, energy security and a level playing field.

AI data infrastructure startup Clairva raises $500K led by Venture Catalysts

AI data infrastructure startup Clairva has raised $500K in a pre-seed funding round led by Venture Catalysts through its angel network. The company will use the fresh capital to strengthen its licensed data supply network, expand partnerships with content owners and institutions, enhance data enrichment and validation capabilities, and support commercial engagement with global AI customers, Clairva said in a press release. Founded in 2025 by Sunil Nair, Sabari Raju, Dushyant Verma, and Amit Parashar, Clairva builds licensed, provenance backed datasets for AI foundation models, embodied AI, robotics, and autonomous systems. As AI models increasingly rely on high quality datasets, sourcing data with clear usage rights, provenance, and cultural context remains a challenge. Clairva works with content owners, production houses, studios, archives, institutions, and contributor networks to source, license, and structure real world data for AI training. The company is initially focused on India, Southeast Asia, and other Global South markets, where languages, environments, behaviours, gestures, workflows, and objects remain underrepresented in AI training datasets. According to Clairva, it is also developing proprietary technology across the data pipeline, including licensed dataset ingestion, rights and provenance tracking, automated enrichment, metadata generation, action and object tagging, temporal segmentation, quality validation, and dataset packaging.

Prosus India posts $781 Mn revenue in FY26; turns adjusted EBITDA positive

Prosus reported a strong performance from its India business in FY26, with the ecosystem turning adjusted EBITDA profitable, driven by fintech platform PayU. According to the Prosus’ FY26 annual report, revenue from its India ecosystem rose 13% year-on-year to $781 million in FY26 from $694 million a year earlier. The business posted an adjusted EBITDA (aEBITDA) profit of $18 million, compared to a loss of $25 million in FY25, while its adjusted EBIT loss narrowed sharply to $10 million from $49 million. The Prosus India ecosystem employed 3,897 people during the fiscal. PayU's payments business generated $577 million in revenue,which grew 10% year-on-year, while delivering EBITDA of $12 million. Higher-margin value-added services (VAS) and SaaS offerings contributed 33% of payments revenue, supporting margin expansion. The company's credit business also reached profitability, reporting an adjusted EBITDA of $6 million. Credit revenue rose 19% year-on-year to $204 million, while new loan issuances touched $221 million during the year. During FY26, PayU processed total payment volume (TPV) worth $90 billion across its platform. The company said PayU accounts for around 25% of India's online payments industry revenue and manages $682 million in assets under management through its lending business. During the year, it also increased its stake in banking payments technology firm Mindgate to 70.7%. Prosus said it is building one of India's most comprehensive digital consumer ecos…

Gambia Trains Journalists on AI in Media as African Union of Broadcasting Assembly Convenes in Banjul

The Gambia’s Ministry of Information, Media and Broadcasting Services, in partnership with the African Union of Broadcasting, has launched a two-day capacity-building programme for Gambian journalists on artificial intelligence and broadcasting, held as part of the 17th General Assembly for journalists in Banjul from April 13 to 16. The training, under the theme “Artificial Intelligence [...]

Zambia Police Warn Against AI-Generated Misinformation Targeting Officials Ahead of 2026 Elections

The Zambia Police Service has warned the public against the creation and circulation of misleading AI-generated content depicting violence and other offensive material aimed at senior public officials. Police spokesperson Godfrey Chilabi said the service had noted with concern the misuse of artificial intelligence to produce deceptive digital content. In a statement issued in Lusaka, [...]

GPT Apps no longer stay active throughout a conversation on Desktop

Hi, We’ve noticed what appears to be a regression in how GPT Apps behave on desktop. Previously, once an app had been invoked in a conversation (for example using @appname ), it remained active for the rest of that conversation. There was no need to invoke it again for every subsequent message. Now, on both: ChatGPT in the browser (desktop) ChatGPT Desktop app the app seems to lose context after every prompt. Unless the app is explicitly invoked again on each message, ChatGPT falls back to either: a regular web search, or its base model knowledge/training. This significantly degrades the user experience, especially for apps designed to support a continuous conversation. Interestingly, this behavior does not seem to occur on the mobile app, where the app appears to remain active across the conversation as before. Expected behavior Invoke the app once in a conversation. All subsequent messages continue using that app until the user explicitly switches away. Current behavior (Desktop) The app must be invoked before every single prompt. Otherwise ChatGPT ignores the app and responds using web search or its default knowledge. Is anyone else seeing the same behavior? Is this an intentional change or a regression? Thanks!

Heatwave: Berlin police use water cannon to cool Bruno Mars fans

Berlin police used a water cannon to cool thousands of Bruno Mars fans queuing outside the Olympiastadion as temperatures soared during Europe's heatwave.

Snupit Leverages Locally Built AI to Connect South Africans With Trusted Service Providers

Artificial intelligence continues to reshape industries worldwide, and South Africa’s online services sector is no exception, with AI increasingly used to help customers find the right businesses faster and more efficiently. Online services marketplace Snupit has been leveraging AI-powered technology for years to improve how customers connect with trusted local service professionals. While many companies [...]

The $411 billion imperative: Why healthcare investment must follow where the patients are

Concern over AI’s impact on Asia’s real estate sector is misplaced

Artificial intelligence (AI) is a transformative force in economies and financial markets. McKinsey estimates that data centres alone will need a staggering US$6.7 trillion in capital investment across the global data centre value chain in the next five years, and the scale of the investment suggests the world economy is in the early stages of a far-reaching shift that could lead to big gains in productivity. In a report on June 24, Vanguard said the massive buildout of AI infrastructure...

Telling internet platforms where to stick public service media will serve nobody. Turn it on its head

Show not tell makes a far finer script

Techie Tonic: Why responsible AI is becoming a boardroom priority

Samsung and SK Hynix plan $590 billion chip investment as AI demand sends memory prices soaring

Samsung and SK Hynix, backed by the South Korean government, are pouring $590 billion into new chip factories and packaging centers as AI data center demand surges. According to Jefferies, memory prices could climb to 50 percent per quarter through 2027. The two companies control nearly 80 percent of the global HBM market. The article Samsung and SK Hynix plan $590 billion chip investment as AI demand sends memory prices soaring appeared first on The Decoder .