Google’s Gemini AI has surged from 5.4% to 18.2% in generative AI web traffic share over the past year, according to Similarweb data, while ChatGPT’s lead has eroded from 87.2% to 68%. This rapid growth positions Gemini as a serious contender in the AI race, driven by strategic integrations across Google’s ecosystem.​

Key Growth Drivers

Gemini’s rise stems from seamless embedding into everyday tools like Chrome, Android, Google Search, Docs, and Gmail, exposing billions of users without requiring separate app downloads. Features such as AI Overviews now reach 2 billion users monthly across 200 countries, boosting daily active users to 35 million by early 2025. Viral innovations like the Nano Banana image editor have further accelerated adoption, displacing ChatGPT as the top free iOS app at times.​

Market Impact

ChatGPT’s decline reflects a maturing AI landscape where first-mover advantage fades against competitors with superior distribution. Alphabet’s stock has outperformed broader markets this year, signaling investor confidence in Gemini’s momentum. Globally, Gemini commands 24% market share among LLM tools, leading in regions like Europe (29% penetration) and India.​

Competitive Landscape

Data compiled from Similarweb trends; Gemini’s native integration gives it an edge over standalone rivals.​

Future Outlook

Gemini’s multimodal capabilities (text, images, audio, video in 46 languages) and enterprise Workspace integrations (2.3B document interactions in H1 2025) suggest sustained growth. As AI shifts to routine utility, Google’s ecosystem dominance could redefine user interactions beyond chatbots. HOI News will monitor updates as the 2026 AI battle intensifies.

Hackers allege theft of 570GB from Red Hat’s consulting repositories, raising concerns over customer exposure.

Red Hat, the open-source software giant owned by IBM, has confirmed a security incident after hackers claimed to have stolen massive amounts of data from its consulting division’s private GitLab repositories. The group behind the attack, calling itself the “Crimson Collective,” alleges that it exfiltrated 570GB of compressed data from over 28,000 internal projects, including sensitive customer documents.

The hackers say they obtained around 800 Customer Engagement Reports (CERs) — detailed consulting documents that may contain network diagrams, architecture plans, credentials, and configuration data from Red Hat’s enterprise clients. Such reports, if authentic, could potentially act as blueprints for attackers to target Red Hat’s customers directly.

Evidence of the breach was shared on Telegram, where the group published file trees, project lists, and snippets from the stolen repositories. They also claimed to have discovered authentication tokens, database URIs, and sensitive secrets embedded within code, which they allegedly used to access downstream customer infrastructure.

Red Hat acknowledged the security incident, confirming that its consulting arm’s GitLab instance was compromised. The company said it has already initiated remediation measures but emphasized that it has found no evidence of a wider compromise affecting Red Hat products, services, or its software supply chain.

In a statement, Red Hat noted:

“We take security incidents very seriously and are actively investigating. At this stage, we cannot verify the attackers’ specific claims, but we are engaging with customers as needed and implementing precautionary steps.”

The Belgian Centre for Cybersecurity has issued an advisory urging organizations that have worked with Red Hat Consulting to rotate credentials, revoke exposed tokens, and review shared configurations. Security experts warn that the leaked CERs could give malicious actors a direct roadmap into client environments.

Industry observers are also raising concerns about Red Hat’s incident response. The attackers allege that their initial disclosures were dismissed or mishandled through routine vulnerability ticketing processes, which may have delayed mitigation.

Adding to the urgency, Red Hat also disclosed a separate critical vulnerability (CVE-2025-10725) in its OpenShift AI platform. With a CVSS score of 9.9, the flaw could allow low-privileged users to escalate to full administrator rights. The company has published mitigation guidance and is working on patches.

The dual challenges — a consulting breach and a critical product vulnerability — highlight the ongoing cybersecurity pressures facing major enterprise vendors. While Red Hat insists its core offerings remain secure, customers are being urged to adopt a cautious approach, particularly those with consulting engagements between 2020 and 2025.

For now, the true scale of the breach remains uncertain. If Crimson Collective’s claims are verified, it could become one of the most serious security incidents to hit the open-source ecosystem in recent years.

From autonomous drones to nuclear fusion startups, artificial intelligence is accelerating breakthroughs in physical technology like never before.

The tech world is experiencing a shift—from screens and software to steel and silicon. A new wave of innovation dubbed “Hard Tech” is making headlines, and at its core is a powerful catalyst: artificial intelligence.

Hard tech refers to industries that merge advanced physical engineering with deep scientific research, such as aerospace, robotics, energy, biotechnology, and manufacturing. These sectors have traditionally required long development cycles, heavy capital investment, and significant regulatory hurdles. But with AI rapidly reducing complexity, cost, and time-to-market, hard tech is experiencing an unprecedented surge.

Startups and corporations alike are integrating AI not just as an add-on, but as the driving engine behind their operations. Autonomous vehicles and delivery drones now navigate cities using real-time AI modeling. In biotech, machine learning algorithms are accelerating drug discovery timelines by years. Even space exploration and nuclear fusion—once limited by guesswork and experimentation—are becoming more predictable through AI simulation and predictive analysis.

One of the standout examples is in the energy sector. Companies like Helion and TAE Technologies are leveraging AI to manage the chaotic variables in nuclear fusion experiments—controlling plasma behavior and optimizing energy output. In transportation, AI is being embedded into robotaxi systems, electric vertical take-off aircraft (eVTOLs), and long-range drone networks, making logistics faster, safer, and more autonomous.

Investors are taking notice. Venture capital firms that once focused on SaaS and mobile apps are now funding next-generation materials, climate tech, and AI-powered robotics. The funding boom in hard tech is being led by figures like Elon Musk, Sam Altman, and Vinod Khosla—who believe the next trillion-dollar innovations won’t come from social media apps, but from real-world disruption enabled by AI.

What makes this surge unique is not just the technology—it’s the mindset shift. Entrepreneurs, scientists, and engineers are no longer working in silos. They’re building cross-disciplinary teams where physicists work with data scientists, and mechanical engineers pair up with neural network experts. The result is faster prototyping, smarter manufacturing, and solutions that are both scalable and impactful.

However, the rise of hard tech also comes with challenges. Building physical products still requires supply chain resilience, regulatory approval, and hardware expertise—areas where traditional tech firms often struggle. There are also ethical concerns around automation, job displacement, and the militarization of autonomous systems.

Still, the momentum is undeniable. As AI continues to mature, it is becoming the great enabler of hard tech—offering the tools to design, simulate, optimize, and operate systems that were once deemed too complex or too costly.We’re entering an era where breakthroughs in physical technologies—from energy to mobility to space—are happening faster and with greater precision than ever before. And at the heart of it all is a single, transformative force: artificial intelligence.