Top Tech News Today: AI & Startup Stories, December 16, 2025

1. China AI Chip Startup Biren Preps Hong Kong IPO as AI Hardware Race Tightens

China’s AI chip startup Biren Technology is preparing to launch a Hong Kong IPO in the coming weeks, aiming to raise about $300 million, according to sources. The company is one of China’s most closely watched attempts to build domestic alternatives to U.S.-linked AI compute stacks, especially as Washington’s export controls continue to squeeze access to advanced hardware and manufacturing routes.

Biren rose to prominence with its BR100 AI chip, which was positioned as competitive with Nvidia’s top-tier data center accelerators. But the company’s trajectory changed after it was added to the U.S. Entity List, which limited access to critical supply chain partners. Despite that, Biren has continued to attract capital and support at home, including a reported early-2025 funding round valuing it around $2 billion. The IPO—led by major banks—signals that investors still have appetite for “sovereign AI” hardware plays, even amid geopolitical headwinds.

Why this matters: If Biren successfully taps public markets, it strengthens China’s push to fund a homegrown AI compute stack and pressures the global chip ecosystem to plan for deeper tech bifurcation.

Source: Reuters.

2. Nvidia Buys Slurm Developer SchedMD in a Big Tech Move to Own More of the AI Stack

Nvidia announced it is acquiring SchedMD, the primary commercial developer of Slurm. This widely used open-source workload manager schedules and optimizes large-scale compute jobs across data centers and supercomputers. Slurm is deeply embedded in research labs and AI infrastructure, and it has become increasingly central as training and inference workloads grow in size and complexity.

What makes this deal especially telling is Nvidia’s posture: the company said Slurm will remain open source, signaling that the acquisition is less about locking down the software and more about tightening Nvidia’s control over the “plumbing” that routes AI workloads onto GPUs. In a world where AI performance is increasingly decided by orchestration, scheduling, and efficiency—not just raw silicon—this is a classic “own the picks and the shovels and the mine entrance” move.

SchedMD’s client list reportedly includes major AI infrastructure players and top supercomputing centers. Financial terms weren’t disclosed, but the strategic message is clear: Nvidia wants to be indispensable not only at the chip layer (GPUs) and programming layer (CUDA), but also at the operations layer where real-world AI clusters live or die.

Why this matters: AI is becoming systems engineering at scale, and Nvidia is positioning itself to capture value from the software layer that determines how efficiently the world’s biggest AI workloads run.

Source: TechStartups via Reuters.

3. US Government Launches ‘Tech Force’ Hiring Push for AI Engineers and Cyber Talent

The U.S. government is launching a major hiring campaign to recruit approximately 1,000 engineers for federal roles on two-year terms, with a focus on AI, cybersecurity, software engineering, and data analytics. The initiative is publicly framed as a modernization sprint: bring in private-sector-caliber builders to upgrade systems, accelerate AI adoption, and strengthen technical capacity inside agencies.

One notable element is the “revolving door” structure embedded in the pitch: the program notes that major private companies—including Apple, Google, and Nvidia—have pledged to consider alumni for roles after their government service. That makes the fellowship more attractive to high-end candidates who might otherwise avoid federal work. Still, it also raises predictable questions about incentives, procurement gravity, and how policy and vendor relationships could blur.

This effort comes at a time when governments worldwide are trying to square a hard circle: they want to regulate AI and cyber risk while also using AI aggressively to improve operations. Those goals collide unless the public sector can recruit, retain, and actually empower top technical talent.

Why this matters: Governments can’t credibly steer AI policy—or defend against cyber threats—if they can’t compete for the same engineering talent shaping the tech landscape.

Source: Reuters.

4. Venezuela’s PDVSA Reports Cyberattack as Oil Logistics Disruptions Surface

Venezuela’s state oil company PDVSA said a cyberattack hit it and publicly blamed the U.S. and domestic collaborators—while also insisting operations were unaffected. However, internal sources told Reuters that systems were still down and disruptions were affecting oil cargo deliveries, creating a gap between official messaging and operational reality.

The event is unfolding amid heightened geopolitical tensions and pressure to enforce sanctions. Even without technical details (PDVSA did not provide specifics on the intrusion method, malware family, or scope), the reported operational impact matters: when energy logistics and scheduling systems go offline, the ripple effects can include delayed loadings, rerouted tankers, and cascading revenue loss—especially for a country where oil exports are a financial lifeline.

In the cybersecurity world, this story follows a familiar pattern: critical infrastructure operators face increasingly frequent attacks, and public attribution often becomes politicized before forensic evidence is released. Whether this was ransomware, destructive wiper activity, credential compromise, or something else, the bigger takeaway is the same: legacy infrastructure combined with geopolitical pressure is a high-risk mix.

Why this matters: Cyber incidents that disrupt energy logistics can rapidly become national-level crises—economically, politically, and operationally.

Source: Reuters.

5. India’s Digantara Raises $50M in Funding for AI-Driven Space Surveillance

Bengaluru-based space-tech startup Digantara raised $50 million in funding to expand its space surveillance capabilities, targeting a global market it described as space monitoring and intelligence. The company develops hardware, software, and AI-driven analytics to track objects in orbit—an increasingly urgent challenge as low Earth orbit becomes more crowded with satellites and debris.

Digantara says it already operates a commercial space-surveillance satellite called SCOT, launched in January 2025, and plans to expand internationally. The round attracted a mix of strategic and financial backers, and the company did not disclose its valuation. The timing is notable: governments and commercial operators are recognizing that space traffic management is shifting from “future concern” to “daily operations” as megaconstellations scale.

Space surveillance is also quietly becoming a geopolitical capability. The same tracking networks that help prevent collisions and protect satellites can also inform defense and intelligence workflows. That means startups in this category may find themselves pulled between commercial demand and national security expectations, especially as regulations mature.

Why this matters: As orbit gets crowded, space surveillance becomes foundational infrastructure—like air traffic control, but with higher stakes and less room for error.

Source: Reuters

6. US Pauses $40B UK Tech Prosperity Deal Covering AI and Quantum

The U.S. has paused implementation of a $40 billion technology agreement with the United Kingdom, Reuters reported. The “Tech Prosperity Deal” covered cooperation in AI, quantum computing, and civil nuclear energy, and was agreed during a September visit. The pause is reportedly linked to Washington’s frustration over the UK’s positions on issues including online safety rules, a digital services tax, and other regulatory concerns.

This matters because these “tech prosperity” frameworks aren’t just symbolic—they often unlock investment narratives, accelerate cross-border collaboration, and create policy alignment that makes it easier for companies to build and deploy frontier tech. A pause introduces uncertainty for firms planning long-horizon investments tied to these agreements, mainly when AI infrastructure buildouts increasingly depend on predictable regulatory pathways.

It’s also a reminder that “tech policy” is now inseparable from trade policy. AI and quantum are treated as strategic assets, and disagreements over digital governance can quickly spill into broader economic leverage.

Why this matters: If major allies can’t keep tech cooperation deals stable, it raises friction for AI and quantum investment—and signals that digital regulation is now a trade bargaining chip.

Source: Reuters.

7. Mirelo Raises $41M to Build AI-Powered Video Translation

Startup Mirelo raised $41 million to build AI-powered tools that translate videos into multiple languages, targeting creators and companies seeking to reach global audiences without rebuilding production pipelines from scratch. The pitch is straightforward: as video becomes the default medium on the internet, language is one of the last remaining barriers to global distribution.

The market timing is real. AI dubbing and translation have moved quickly from novelty to business necessity, especially for education, product marketing, and creator economies that increasingly want “one video, many markets.” The challenge, as always, is quality: natural-sounding voice, accurate meaning (not just literal translation), and lip-sync realism. The category is also competitive, with incumbents and new startups racing to become the default localization layer for video.

Mirelo’s raise suggests investors still see headroom in applied media AI—especially tools that drive direct ROI through expanded reach and higher engagement. But the bigger strategic question is whether these companies become durable platforms or get absorbed into larger creator suites.

Why this matters: AI translation is turning distribution into a software problem—shrinking the cost of going global for every creator and marketing team.

Source: TechStartups

8. Chai Discovery Lands $130M to Accelerate Drug Development

Biotech startup Chai Discovery raised $130 million to build AI-driven systems to accelerate parts of drug discovery and development. Investors continue to pour capital into biology-meets-compute plays, betting that model-driven discovery and simulation can reduce timelines, improve hit rates, and lower the cost of early-stage research.

The strategic logic is compelling: pharma R&D is expensive, slow, and failure-prone. If AI systems can better predict molecular behavior, generate viable candidates faster, or prioritize experiments more efficiently, the value created would be enormous. But the sector is also littered with hype cycles, which is why execution and validation matter: real pipelines, credible partnerships, and clinical progress.

What keeps this category hot is that it doesn’t rely on consumer adoption or ad markets. If it works, it plugs into a trillion-dollar industry with clear buyers and clear incentives. At the same time, the science is brutal—biology often refuses to cooperate with clean abstractions—and regulatory scrutiny is high once you move toward clinical decisions.

Why this matters: AI in biotech is one of the few categories where better models can translate into real-world outcomes: faster medicines, lower costs, and new therapeutic options.

Source: TechCrunch.

9. Thea Energy Previews AI-Controlled Fusion Power Plant Design

Fusion startup Thea Energy previewed “Helios,” a fusion power plant concept built around a stellarator-style approach using arrays of smaller magnets and AI-powered control software to tune the magnetic fields. The idea is to reduce the manufacturing and precision burden that makes many fusion designs costly and challenging to scale.

The company argues that instead of crafting highly bespoke magnet structures, it can use many smaller, identical superconducting magnets and let software compensate for imperfections—essentially turning fusion hardware complexity into a control problem. The plan includes an initial device (“Eos”) intended to validate the physics, with a site announcement planned for 2026 and a longer timeline toward activation around 2030.

Fusion remains a high-risk, high-reward frontier. The prize is massive—firm, clean power at grid scale—but the engineering realities are unforgiving: materials, maintenance cycles, heat-handling, and cost competitiveness with wind, solar, and storage. Still, this is why investors and policymakers keep watching: even modest breakthroughs could reshape energy markets and AI infrastructure economics.

Why this matters: If fusion becomes cheaper to build through software-controlled designs, it could unlock a new class of clean baseload power—right as AI drives electricity demand higher.

Source: GlobeNewswire.

10. Ford Spins Up Battery Storage Business as Grid Demand Surges

Ford is launching a battery storage business, positioning itself to sell energy storage systems that can support grid stability and help manage rising electricity needs. The move reflects a broader trend: as EV adoption grows and AI data centers expand, the grid is under pressure—and batteries are becoming core infrastructure, not just car components.

For automakers, storage is a logical adjacency. They already understand batteries, supply chains, safety, and lifecycle management. The opportunity is also financial: storage can generate recurring revenue through partnerships with utilities, commercial operators, and industrial customers. But it’s a competitive landscape with specialist players, utilities building in-house capabilities, and global battery giants pushing their own turnkey systems.

The long-term bet is that energy management becomes as strategically important as mobility. If Ford can build a credible storage brand and stack services on top—monitoring, optimization, financing—it could diversify beyond cyclical vehicle sales.

Why this matters: Batteries are becoming the “new infrastructure,” and automakers that move early into storage can capture a second growth engine beyond cars.

Source: Bloomberg

11. Chicago Tribune Sues Perplexity AI as Publisher Backlash Escalates

The Chicago Tribune filed a lawsuit accusing Perplexity AI of copyright infringement, arguing that AI-generated answers improperly reproduce or republish its journalism, diverting traffic and revenue. The complaint follows similar moves from major publishers and signals that courts are becoming a key battleground for the future of AI search and “answer engines.”

This fight isn’t only about training data—it’s about outputs. Publishers are increasingly focused on whether AI products can summarize, quote, or restate reporting effectively enough that users stop clicking through to the sources. That goes straight to the business model of digital journalism, which depends on audience attention, subscriptions, and advertising.

For AI companies, the stakes are existential: if courts impose strict limits on retrieval, summarization, or presentation, many consumer-facing AI search products will need licensing deals, new technical guardrails, or major redesigns. Expect more lawsuits, more settlements, and a growing market for content licensing—especially as regulators and lawmakers get pulled into the debate.

Why this matters: This legal wave could define what AI search is allowed to do—and whether publishers get paid or get disintermediated.

Source: Axios.

12. Disney Strikes OpenAI Deal in One-Year Exclusive Arrangement

Disney has reached a deal with OpenAI under a reported one-year exclusive arrangement, signaling how aggressively major entertainment players are moving to secure AI capabilities while controlling the terms. The strategic tension is evident: studios want AI’s productivity upside (production workflows, localization, marketing, creative tooling), but they also wish to have ironclad protection around IP and brand integrity.

Exclusivity is the tell. Disney isn’t just “testing” generative tools; it’s treating AI as a strategic vendor relationship worth locking down—at least temporarily. That also puts pressure on other model providers and entertainment companies to strike their own partnerships, accelerating a “platform alignment” era where big brands choose sides based on trust, policy, and product fit.

The deal also comes amid intensifying legal and labor scrutiny of AI in the creative industries. Partnerships that emphasize enterprise controls, provenance, and rights management are likely to become the default model for large media firms.

Why this matters: When Disney moves, it sets patterns—this is AI going enterprise at the highest level of IP sensitivity.

Source: TechStartups via Disney Newsroom

13. Google Is Turning Off ‘Dark Web Report’ Feature

Google is ending its “dark web report” feature, a consumer security tool that helps users determine whether their personal data appears in specific breach-related contexts. The move highlights a recurring challenge in consumer security: even well-intentioned features can struggle with scope, maintenance costs, liability concerns, and user comprehension.

Dark web monitoring is also a crowded space—many password managers and identity protection services offer similar alerts, often bundled into paid subscriptions. Google’s step back may signal a shift toward prioritizing core account protections (passkeys, phishing defenses, security checkups) rather than maintaining a separate “monitoring” product that users may not fully understand or consistently use.

For users, the practical implication is simple: fewer built-in alerts from Google means relying more on third-party services, credit monitoring, or proactive hygiene measures such as unique passwords and passkeys. For the industry, it’s another reminder that breach exposure has become a permanent layer of modern life—and product decisions about “who monitors what” are increasingly strategic.

Why this matters: Consumer security tools live or die on trust and clarity, and Google’s retreat leaves a gap others will rush to fill.

Source: TheVerge.

14. GM Brings Native Apple Music to Cadillac and Chevy Models

General Motors is rolling out native Apple Music support to select 2025 and 2026 Cadillac and Chevrolet vehicles via over-the-air updates, continuing its strategy of expanding in-car native apps. The move fits within a broader narrative: GM has been pushing deeper into its own infotainment ecosystem, particularly as it reduces reliance on phone mirroring in certain models.

The arrival of Apple Music as a native integration (rather than phone projection) matters for user experience—hands-free controls and deeper system integration. It features Dolby Atmos/spatial audio support in compatible setups. GM says the app will be included in its OnStar Basics package, offered free for a multi-year period on eligible vehicles, and that other brands, such as Buick and GMC, will follow later.

This is also a signal about control. Car dashboards are turning into software platforms, and automakers want the leverage that comes with owning distribution, data, and subscription surfaces. Whether consumers accept that trade—native apps instead of “my phone, my rules”—remains a key battle in automotive tech.

Why this matters: The car is becoming a software platform, and native media apps are a key wedge in the fight over who owns the in-vehicle experience.

Source: The Verge.

15. LG Debuts Micro RGB evo TV to Challenge Premium Display Rivals

LG announced its first flagship RGB LED television line, the Micro RGB evo TV, which is expected to launch in 2026 in large-format sizes. The company is entering the RGB LED market as premium TV makers experiment with new backlighting architectures that promise stronger color performance and brightness—especially as consumers compare OLED to evolving LED alternatives.

LG’s positioning is also about education: it emphasized that “Micro RGB” isn’t the same as microLED. The display approach uses clusters of red, green, and blue LEDs to illuminate groups of pixels (still relying on a color filter), rather than microLED’s “one LED per pixel” ideal. The inclusion of an upgraded processor and color-gamut certifications aims to position this as a no-compromises flagship, not a niche experiment.

For the market, the bigger signal is momentum: multiple major manufacturers are now shipping or planning RGB LED models, increasing the odds that prices come down and sizes broaden, which is what it takes for any new display class to become mainstream.

Why this matters: Premium TV tech is entering a new cycle, and RGB LED is shaping up as the next battleground for brightness and color leadership.

Source: The Verge

Closing

That wraps today’s tech briefing — a sharper look at how power, capital, and control are reshaping AI, infrastructure, security, energy, space, and the global startup economy. The signal cutting through the noise is clear: AI is no longer a speculative bet or a marketing slogan. It has become a baseline requirement, driving real-world decisions about data centers, electricity, chips, and national competitiveness. The money flowing into compute, scheduling software, fusion energy, and space infrastructure isn’t chasing hype — it’s buying leverage for the next decade.

Policy and geopolitics are no longer operating at the edges of the tech sector. They are embedded directly in the stack. From stalled international tech agreements to courtroom battles over AI-generated content and tighter government control over talent and exports, the rules of engagement are being rewritten in real time. For global operators, growth now depends as much on regulatory alignment and trust as on technical execution.

AI’s expansion into the physical world is accelerating the stakes. Software-driven decisions increasingly shape energy grids, orbital space, biotech pipelines, and transportation systems, while cyber incidents continue to demonstrate how fragile these systems become when security lags capability. Each failure now carries economic and geopolitical consequences, not just reputational ones.

The pattern across today’s stories is unmistakable: AI has become the organizing force of modern industry. The winners will be those who can coordinate compute, power, security, and credibility at scale. Everyone else will be forced to operate in a landscape where the pace of technological change outpaces the institutions meant to govern it.