Top Tech News Today: AI & Startup Stories, December 17, 2025

Technology News Today – Your Daily Briefing on the AI, Big Tech, and Startup Shifts Reshaping Markets

It’s Wednesday, December 17, 2025. We’re back with a focused look at the forces reshaping the global tech landscape — from accelerating AI infrastructure bets. Big Tech power plays to mounting cybersecurity threats, regulatory pressure, and the growing energy demands behind modern computing.

Today’s headlines reflect an industry pushing deeper into a scale-driven phase. Databricks’ multibillion-dollar raise at a nine-figure valuation underscores how data infrastructure has become one of the most defensible layers in the AI stack, while Amazon’s reported talks of a massive OpenAI investment highlight how cloud giants are racing to secure strategic control over frontier models. Google and OpenAI’s intensified push into India signals that AI competition is no longer just about benchmarks, but about global user acquisition, language coverage, and data gravity.

At the same time, the operational realities of AI adoption are becoming harder to ignore. Energy constraints are shaping where data centers get built, with long-term renewable power deals now as strategic as chips. Security risks are escalating as AI-assisted cyberattacks move toward automation, forcing governments and enterprises to rethink threat models. Privacy regulators in Europe are sharpening enforcement, putting renewed pressure on ad tech, app tracking, and platform compliance. At the same time, app-store economics remain under scrutiny as developers push back against entrenched fee structures.

Beyond software, AI’s influence continues to spill into frontier categories — from climate-tech logistics and battery manufacturing to semiconductor supply chains and global hardware production shifts. Venture markets remain split, with mega-rounds and late-stage capital flowing to infrastructure leaders even as most founders face tighter fundraising conditions.

Taken together, today’s developments show a tech sector moving decisively from experimentation to execution — where capital intensity, regulation, energy, and trust now shape the pace of innovation as much as technical capability itself.

Here’s your complete breakdown of the 15 latest technology news stories shaping the market today.

Technology News Today

1. AI Startup Databricks Raises $4B at a $134B Valuation to Expand Its Data + Model Platform

Databricks just added fresh rocket fuel to the “AI infrastructure” arms race, announcing it raised more than $4 billion in a Series L round at a $134 billion valuation. The company sells a platform that helps enterprises manage massive datasets and build or run AI models on top of them, making data plumbing one of the most lucrative layers of the AI stack. Databricks said the new valuation is a sharp step up from its $100B valuation in a prior round earlier this year, underscoring how quickly investor appetite is clustering around a small set of “AI picks-and-shovels” winners.

What makes this meaningful is not just the headline number, but what the funding signals: big buyers are still spending aggressively on modern data architectures as they shift from experimenting with AI to deploying it across core workflows. Reuters reports that Databricks crossed a $4.8B revenue run rate in Q3 and noted that the company delivered positive free cash flow over the last 12 months. That combination—growth plus cash discipline—has become the new gold standard in late-stage tech, especially as the market tries to separate sustainable AI businesses from hype. The company said it will use the funds to expand research and retain talent, a direct nod to how competitive (and expensive) the AI labor market remains.

Why It Matters: Databricks’ mega-round is a loud signal that investors still believe the “enterprise AI backbone” layer will mint category-defining giants.

Source: TechStartups via Reuters and Databricks.

2. Amazon in Advanced Talks to Invest Over $100 Billion in OpenAI

Amazon is reportedly in talks to invest more than $10 billion in OpenAI, a move that would reshape the competitive geometry of the AI platform wars. On the surface, it looks like another giant check in an industry already drowning in capital. Below, it’s about leveraging cloud scale, distribution, and control in the next generation of developer ecosystems. If Amazon deepens its financial ties to OpenAI, it could create new strategic pressure on Microsoft (already a major OpenAI partner) and intensify the battle among the largest clouds to be the default home for AI workloads.

The timing matters because hyperscalers are facing multiple fronts simultaneously: model access, proprietary chips, data center capacity, and enterprise relationships. A deal of this magnitude would likely have implications for compute commitments, go-to-market bundling, and how quickly OpenAI can scale its product offerings across global markets. In practical terms, the “winning” AI platforms will be those that combine frontier capabilities with enterprise reliability, compliance posture, and cost-effective, predictable inference at scale. That requires capital, yes—but also supply chains, power contracts, and global infrastructure. Amazon is one of the few companies on earth that can industrialize that entire stack.

Why It Matters: If Amazon seriously backs OpenAI at this scale, the AI platform race becomes even more concentrated around a handful of mega-alliances.

Source: The Information, CNBC, and TechStartups

3. OpenAI and Google Use Freebies to Win India’s Users (and Training Data)

OpenAI and Google are intensifying their push into India with promotions and “freebie” strategies designed to acquire users at scale—because India is not just a market; it’s a data and distribution battleground. Reuters reports the competition is partly about winning Indian users and, crucially, securing more training data and real-world usage signals that help models improve. In a world where model performance can hinge on access to diverse language inputs, cultural context, and long-tail queries, India’s scale becomes a strategic asset.

This matters because it shows how the AI race is evolving beyond Silicon Valley product launches into global market capture, where pricing and bundling become weapons. The winners won’t just have the best benchmarks; they’ll have the deepest user adoption in the regions where the following billion internet users live. India also creates a forcing function around multilingual AI, voice-first interfaces, and low-bandwidth realities—areas where “lab-grade” demos often break in the wild. As these companies race to onboard users, regulators and civil society will also scrutinize consent, data handling, and the destination of training data. For founders, the signal is clear: India is becoming a frontline market for AI distribution, partnerships, and localized products—not an afterthought.

Why It Matters: India is emerging as a decisive AI growth market—whoever wins adoption there gains a durable product advantage and data gravity.

Source: Reuters.

4. Google Launches “CC,” an AI Agent That Builds a Personalized Morning Briefing From Your Gmail and Calendar

Google is rolling out an experimental AI agent called CC that aims to replace your morning scroll with a tailored daily briefing generated from your emails, calendar, and documents. According to The Verge, CC delivers a “Your Day Ahead” summary that highlights key tasks, appointments, and bills, and can also draft emails or create calendar links so users can act quickly. It’s initially offered to paid subscribers (18+) in the US and Canada on a waitlist.

This is a crucial product signal because it shows Google pushing AI from “search and chat” into “life operating system.” The assistant isn’t just answering questions—it’s interpreting your personal context and proactively producing outputs that shape your day. That raises obvious privacy and trust questions (the assistant needs deep access to sensitive personal data). Still, it also shows why Google believes it can compete in agentic AI: it already owns the workspace layers where your life is stored. The Verge notes CC is built on Google’s Gemini models and resembles a personalized briefing product OpenAI launched earlier this year, highlighting how the biggest AI labs are converging on “daily workflow agents” as the next distribution wedge. If this works, it could make the inbox and calendar even more central—and shift attention away from social feeds toward AI-curated personal dashboards.

Why It Matters: AI is moving from “tools you use” to “agents that run your day,” and Google is weaponizing its workspace footprint to get there first.

Source: The Verge

5. OpenAI Launches GPT Image 1.5, Its New Flagship Image Generator to Counter Google’s Nano Banana

OpenAI has launched GPT Image 1.5, positioning it as a new flagship image generation model designed to be faster, more accurate with instructions, and better at editing existing photos. The Verge reports that the model can generate results up to four times faster, improves instruction-following, and is positioned as especially useful for enterprise use cases—such as product visuals and practical image edits rather than novelty art. OpenAI also added a dedicated Images tab to ChatGPT, featuring preset filters and trending prompts.

The strategic story here is margin and defensibility. Image generation has become brutally competitive, with multiple labs racing to win creative tooling, advertising workflows, and commerce content production. By emphasizing “useful edits” and business-grade output, OpenAI is trying to own the professional layer: marketing teams, e-commerce catalogs, design systems, and internal creative operations. The Verge notes OpenAI framed the update as a shift toward “practical, high-fidelity visual creation,” part of a broader push to become a profitable, durable platform under investor pressure. If GPT Image 1.5 improves reliability and edit precision, it makes it easier for companies to integrate image generation into repeatable pipelines (where recurring spend lives) rather than one-off experiments. The “enterpriseization” of image models is a big step toward AI that quietly replaces labor in production workflows—not just AI that makes viral demos.

Why It Matters: The next phase of generative media is about dependable production work, and OpenAI is explicitly chasing that enterprise budget.

Source: The Verge

6. TikTok Accused of Tracking Grindr Activity Via a Third-Party Ad/Analytics Tool

A privacy advocacy group filed complaints in Austria alleging that TikTok, Grindr, and AppsFlyer violated EU privacy rules by tracking user activity across apps without proper consent, potentially exposing sensitive data. Reuters reports the group noyb claims the cross-app tracking breached GDPR and that TikTok used the data for advertising and analytics. The story lands in an already tense environment for TikTok in Europe, where the company has faced significant regulatory scrutiny and penalties.

This matters because cross-app tracking isn’t just “ad tech drama”—it’s a real-world risk multiplier when the data involves sensitive contexts like sexual orientation, dating patterns, or location-linked behavior. Even if systems are designed for “analytics,” the downstream effect can be profiling, inference, or unintended leakage. Regulators in Europe have signaled that consent theater won’t cut it, and privacy groups are getting increasingly sophisticated at identifying how trackers operate across ecosystems. Reuters notes that TikTok was previously fined 530 million euros by Ireland, adding weight to new allegations. If authorities pursue the complaints aggressively, it could trigger renewed enforcement, operational constraints on tracking infrastructure, or stricter compliance requirements for third-party attribution tools. For the broader industry, this is another reminder that privacy regulation is not slowing down—it’s becoming a competitive factor that can reshape product analytics, ad performance, and platform growth tactics.

Why It Matters: Europe is tightening the screws on cross-app tracking, and sensitive-data allegations can quickly escalate into major regulatory and reputational damage.

Source: Reuters.

7. Developers Push Regulators to Clamp Down on Apple’s App Store Fee Practices

A coalition of 20 app developers and consumer groups is urging European regulators to enforce the Digital Markets Act (DMA) against Apple, arguing Apple’s fee structure harms European developers—especially after a recent U.S. court decision changed the competitive landscape. Reuters reports the coalition claims Apple’s approach disadvantages EU developers relative to U.S. rivals and calls for stronger enforcement of rules requiring “gatekeepers” to allow alternatives to in-app payments without penalty

The business impact is enormous because the DMA is not a symbolic law—it’s designed to break default platform tollbooths. If regulators decide Apple’s fees or compliance structure violates the DMA’s intent, it could force changes to how Apple monetizes distribution, payments, and customer relationships in the EU. That would ripple through subscription economics, ad-driven apps, and indie developer viability, particularly for companies that can’t afford high acquisition costs and rely on margin efficiency. The bigger story: global app commerce is being rewritten by overlapping legal regimes (U.S. court rulings, EU DMA enforcement, and potentially parallel moves in other jurisdictions). For startups, this uncertainty is painful but also creates opportunities: alternative payments, web-to-app funnels, and new distribution strategies can suddenly become viable—or risky—depending on the enforcement posture. Today’s pressure campaign shows developers are not waiting quietly; they’re pushing regulators to turn the DMA from theory into action.

Why It Matters: The EU is shaping the future economics of the App Store, and Apple’s next compliance moves could alter margins across the entire app ecosystem.

Source: Reuters.

8. Apple Reportedly Talks With Indian Chipmakers to Package iPhone Components in India

Apple is in early discussions with Indian chipmakers about assembling and packaging iPhone components in India—potentially including display chips—according to a Reuters report. The talks involve Murugappa Group-owned CG Semi, which is building an outsourced semiconductor assembly and test (OSAT) facility in Gujarat. Reuters notes this would be the first time Apple has considered assembling and packaging some chips in India.

This is strategically significant because the semiconductor value chain is being rebalanced in real time. For Apple, expanding OSAT capability in India isn’t just about cost—it’s about supply resilience, geopolitical risk management, and accelerating India’s role from “assembly hub” to deeper participation in high-value electronics manufacturing. Packaging and testing are critical steps that affect yield, performance, and supply flexibility, and bringing these capabilities closer to final assembly can shorten cycle times and reduce bottlenecks. For India, landing even partial iPhone chip packaging work reinforces its industrial ambitions beyond smartphones into semiconductors and advanced manufacturing—areas where government incentives and global realignment are pulling investment. For the broader market, it’s another marker that “China+1” isn’t a slogan anymore; it’s a structural supply chain rewrite that could shape component pricing, capacity planning, and technology transfer across Asia for years.

Why It Matters: Apple’s move to chip packaging discussions in India signals a deeper supply-chain shift that could reshape where advanced electronics value is created.

Source: Reuters.

9. TotalEnergies Signs a 21-Year Deal to Power Google Data Centers in Malaysia

TotalEnergies has signed a 21-year power supply deal with Google to provide one terawatt-hour of renewable energy for Google’s data centers in Malaysia, Reuters reports. The energy is expected to come from a new solar plant (Citra Energies) scheduled for construction in early 2026. The deal is another concrete example of how AI-era compute growth is forcing Big Tech to lock in long-term power with a credible low-carbon supply.

This is a big deal because “AI expansion” is now constrained by electricity as much as by chips. Data centers—especially those running large-scale AI training and inference—are power-hungry, and the biggest operators are learning that you can’t scale reliably without direct relationships to generation assets and long-duration contracts. Long-term PPAs (power purchase agreements) also help companies de-risk price volatility and satisfy climate commitments that investors and regulators increasingly track. Malaysia is becoming a more critical node in the regional data center map, and power availability will influence where future capacity gets built. For startups and cloud-dependent businesses, these deals matter indirectly: power constraints and energy costs eventually flow downstream into cloud pricing, availability, and regional performance. This is “infrastructure reality” catching up to AI ambition.

Why It Matters: The AI boom is becoming an energy story, and long-term renewable contracts are now a core competitive advantage in cloud infrastructure.

Source: Reuters.

10. Tesla Expands Battery Cell Investment at Its German Gigafactory as Europe’s EV Competition Tightens

Tesla is ramping up battery cell investments at its German gigafactory, Reuters reports, signaling continued commitment to European manufacturing even as the EV market becomes more price-competitive and politically sensitive. While Reuters’ brief notes the expansion, the broader context is that battery economics—cost per kWh, yield, and localized supply—often determine whether EVs can be priced competitively without sacrificing margins.

This matters because Europe is now a battleground where industrial policy, supply chains, and consumer demand collide. Localizing battery production can reduce exposure to logistics shocks and tariffs, improve delivery predictability, and position Tesla to respond more quickly to regional demand shifts. It can also help Tesla navigate a landscape where European automakers and Chinese entrants are competing for market share, and where regulators are increasingly focused on domestic value creation. Battery investments also signal Tesla’s confidence in long-term capacity utilization, a strong statement at a time when parts of the auto industry are still debating the pace of EV adoption. For the broader tech ecosystem, this story reinforces a theme: the next decade’s winners will be those who can industrialize advanced technology—energy storage, manufacturing automation, and software-defined products—at scale, under real-world constraints.

Why It Matters: Battery investment is EV strategy in physical form—and Tesla is reinforcing its European footprint, where manufacturing and policy matter as much as software.

Source: Reuters.

11. ShinyHunters Threatens to Expose Pornhub Premium User Data in a Bitcoin Extortion Attempt

The hacking group ShinyHunters is threatening to expose data tied to Pornhub premium users and demanding payment in bitcoin, Reuters reports. The story is especially alarming because of the stigma-driven coercion angle—where attackers rely on reputational fear, not just financial loss, to force compliance. Reuters reports that it partially authenticated some of the stolen data, which adds credibility to the threat and increases pressure on the company involved.

This incident is a reminder that “data breach harm” isn’t evenly distributed. In breaches involving sensitive services, the risk isn’t just identity theft; it’s blackmail, harassment, doxxing, and long-term personal safety implications. For enterprises, this is another warning that attackers often target victims who are least likely to report or challenge extortion, because shame and fear do the attacker’s work for them. Reuters notes ShinyHunters has a history of extortion attempts against multiple victims, reinforcing that this is not a one-off event but part of a repeatable criminal playbook. For the cybersecurity industry, the pattern is clear: perimeter defenses aren’t enough, and incident response now includes legal strategy, customer protection, and communications discipline. For policymakers, it will intensify debates around breach notification, data minimization, and more substantial penalties for cyber extortion operations.

Why It Matters: Sensitive-data breaches can create real-world coercion at scale—and extortion groups are increasingly targeting exactly that pressure point.

Source: Reuters.

12. HashKey’s Hong Kong Trading Debut Shows How Volatile Regulated Crypto Finance Still Is

Crypto exchange HashKey had a volatile trading debut in Hong Kong, with shares ending roughly flat after earlier gains, Reuters reports. The listing is notable because Hong Kong has positioned itself as a more regulated, institution-friendly crypto hub, seeking to attract capital and credible operators while distancing itself from the “wild west” image that still haunts the sector. A public-market debut in that environment is a test: not just of one company’s fundamentals, but of investor confidence in the region’s broader crypto framework. Reuters

Volatility matters because the industry is still in transition. Regulation is tightening, exchanges are being pushed toward transparency, and investors are demanding stronger governance than in the last cycle. Yet market behavior still swings hard on sentiment, liquidity conditions, and macro risk—especially for crypto-linked equities. A “flat” finish after a volatile day can be read two ways: either stabilization (investors aren’t rushing in blindly) or uncertainty (the market is still pricing the sector’s long-term risk premium). Either way, listings like this serve as reference points for other crypto firms considering public markets and for policymakers assessing whether regulation can foster healthier capital formation without stifling innovation. It’s also a reminder for founders: in fintech and crypto, credibility is now a product feature—and markets reward it inconsistently, but they punish its absence fast.

Why It Matters: Even in “regulated crypto” markets, public listings show just how fragile confidence remains—and how quickly it can swing.

Source: Reuters.

13. Freshworks Eyes Acquisitions With an $800M Cash Pile as AI Reshapes Customer Support Software

Freshworks is signaling it wants to be a buyer, not a bystander, in the AI-driven reshaping of enterprise software. Reuters reports that the company is exploring acquisitions while holding roughly $800 million in cash, with AI explicitly in focus. In customer support and IT service management, AI isn’t a feature anymore—it’s becoming the product: automated triage, agent assist, and fully automated resolution workflows are now table stakes for competing with larger incumbents.

This matters because the customer support stack is undergoing a structural shift. AI can significantly reduce costs (fewer human touches), improve response times, and enable smaller teams to handle higher ticket volume. That creates a “winner-take-most” dynamic in which platforms that successfully integrate AI into end-to-end workflows can quickly capture market share. The acquisitions angle is also telling: instead of building every AI capability in-house, Freshworks is considering buying speed—whether that’s proprietary automation tech, vertical-specific workflows, or data assets that improve model performance. In a market where Salesforce and other giants are moving aggressively, Freshworks’ cash position gives it optionality to shape its own destiny. For startups, it’s also a clear signal: high-quality AI-native workflow companies (especially in service, IT, and back-office operations) are increasingly attractive M&A targets as incumbents rush to keep up.

Why It Matters: AI is reshaping the support software category, and Freshworks is using cash and M&A to avoid being boxed out by larger platforms.

Source: Reuters.

14. Amazon and Whole Foods Back AI-Driven Food Recycling Tech With a Rollout Plan Through 2027

Amazon and Whole Foods are partnering with Mill to deploy AI-enhanced food recycling bins across Whole Foods stores by 2027, Axios reports, and Amazon is also investing an undisclosed amount in the startup. Mill says it has raised $250 million total, with investors including Amazon’s Climate Pledge Fund and other principal climate-focused backers. The system aims to make food-waste processing more efficient and scalable—an overlooked climate problem that is often overlooked.

Why this matters is scale and behavior change. Food waste is notoriously hard to reduce because it’s distributed—homes, restaurants, and grocery stores all generate it in fragmented ways. A retail rollout provides the technology with a distribution channel that can improve waste handling without relying on individual consumers to handle everything perfectly. Axios also highlights the climate stakes: the UN estimates that food loss and waste account for a significant share of global emissions and impose massive economic costs. If AI and better hardware can reduce contamination, improve routing, and make composting or recycling more operationally reliable, it turns “green intention” into “repeatable logistics.” For Amazon, it’s also a brand and supply chain story: reducing waste can improve efficiency, reduce hauling costs, and strengthen sustainability claims at a time when Big Tech’s climate footprint is under the microscope amid data center growth.

Why It Matters: Climate tech wins when it gains distribution—and Whole Foods provides an AI-powered waste-reduction rollout channel.

Source: Axios.

15. Researchers Warn AI Models Are Getting Better at Hacking, Faster Than Defenses Are Adapting

New research and industry warnings suggest AI systems are rapidly improving at offensive cyber capabilities—pushing the industry closer to a world where AI-enabled attacks can scale with minimal human input. Axios reports that the prospect of models executing cyberattacks “fully on their own” is becoming increasingly likely, and notes that leaders from Anthropic and Google are set to testify before House Homeland Security subcommittees on how AI is reshaping the threat landscape. Axios also quotes Anthropic’s red team leadership warning this may be an early indicator of attacks growing in sophistication and scale—even with safeguards.

This is one of the most essential “second-order” AI stories because it’s not about a flashy product launch—it’s about capability diffusion. As models become more capable at code generation, system reasoning, and tool use, the same skills that help developers ship faster can help attackers discover vulnerabilities, craft exploits, automate phishing, and iterate payloads with frightening speed. The scary part is the asymmetry: defenders have to be right every day, across sprawling systems; attackers only need a few wins. And if AI reduces the cost of running attacks, we may see a volume explosion that overwhelms already understaffed security organizations. The policy angle matters too: once this becomes a national-security narrative, it can drive regulation, reporting mandates, and pressure on AI labs to harden models against misuse—while also pushing enterprises to accelerate security modernization.

Why It Matters: AI doesn’t just boost productivity—it can industrialize cybercrime, and governments are treating that risk as urgent.

Source: Axios.

Closing

That’s your tech briefing for today — a concise snapshot of the forces steering the industry across AI, cloud infrastructure, cybersecurity, energy, and the global startup economy. Today’s developments reinforce a clear shift: AI is no longer being tested at the margins; it is actively reorganizing how companies view compute, data, power, and scale as core constraints.

Across markets, infrastructure decisions are driving competitive advantage. Capital is flowing toward platforms that control data pipelines, energy access, and deployment reliability, while volatility in public and private markets indicates that scale must be matched by credible economics. At the same time, regulation and geopolitics are playing a larger role, with governments tightening expectations around security, privacy, and compliance, pushing companies to mature faster under scrutiny.

AI’s footprint is also expanding beyond software into the physical world — from energy systems and manufacturing to cybersecurity and climate-focused logistics. The common thread is unmistakable: AI is no longer a momentum story. It’s a mandate. The next decade will be defined by companies that can align technology, capital, trust, and infrastructure — and adapt quickly as the pace of change continues to accelerate.