In April, a federal judge said that Google illegally dominated two markets for online advertising technology.

Google says it will appeal online search antitrust decision

Pride Toronto has faced another setback, losing two more major corporate sponsors — Google and Home Depot — just before Pride Month begins, Pride Toronto executive director Kojo Modeste told CP24 Saturday afternoon.

Google, Home Depot pull sponsorship from Pride Toronto

Google has fixed a bug in Wear OS that forced users to authenticate multiple times after each contactless payment. More details here.

Google Fixed a Bug That Made You the Most Hated One in Checkout Lines

States across the US are slowly rolling out support for adding your driver’s license or ID to the Google Wallet app on Android.

Where Google Wallet state IDs are available on Android

“We interact in person with the company to answer one fundamental question: can we add value to this company at this stage? And if the answer is yes, the likelihood of them making it is high.”

How Google Is Helping AI Startups Scale in India

NEW YORK — Google on Friday urged a US judge to reject the notion of making it spin off its Chrome browser to weaken its dominance in online search.

Google makes case for keeping browser

German motorists likely felt disheartened at the sight of all the stop signs on Google Maps on Thursday. The Guardian reports that major roads in western, northern,...

German roads thrown into chaos after Google Maps mislabels highways as closed

Last week, Google quietly released an app, Google AI Edge Gallery, that lets users run a range of openly available AI models from the AI dev platform Hugging Face on their phones.

Google quietly released an app that lets you download and run AI models locally

Both Google and DOJ shared their closing arguments during the final day of the remedies case regarding Google's Search monopoly.

Final Shots Fired in Google’s Search Monopoly Trial-Verdict Coming This Summer

Forget Google Keep, OneNote and Evernote, 5 reasons NotebookLM is the future of note-taking

Google

google

The Internet Facebook, ChatGPT, Tiktok & Google Don't Want You To See

Google’s launch of Gemini CLI could be an defining moment for Google’s broader business strategy in AI. The move reflects Google’s attempt to create a distribution and engagement engine for Gemini models, much like Apple’s App Store created a lasting ecosystem around the iPhone. If Google succeeds, Gemini CLI could become a key on-ramp for businesses and developers to integrate Gemini-powered AI into the products and services they build. Gemini CLI Gemini CLI For years, Google has been known for AI research leadership, but it has struggled to convert that leadership into widely adopted, developer-facing tools. Gemini CLI is Google’s most direct attempt yet to change that by putting AI into the terminal, where developers spend much of their time building, testing, and deploying software. More broadly, Gemini CLI reflects an industry trend: AI tools are shifting from standalone chat interfaces to embedded, workflow-integrated systems. For Google, the stakes go beyond developer adoption. Gemini CLI represents a chance to make Gemini foundational to how businesses build software, and how they engage with Google’s AI platform for years to come. Why Google Needs Gemini CLI to Succeed Why Google Needs Gemini CLI to Succeed Google has been known for AI breakthroughs in research papers and large language models, while OpenAI, Microsoft, and GitHub have moved faster in getting AI tools into developers’ hands. Products like GitHub Copilot and ChatGPT’s code interpreter have already shaped how many developers write and test code. These tools are becoming the default assistants for developers tackling everything from simple scripting tasks to complex application builds. Google’s challenge involves more than releasing new AI features. The company also needs to shift developer perception and usage patterns. Gemini CLI gives Google a foothold in the environments where developers already work, offering a way to make its AI models more practical, usable, and visible in day-to-day software engineering. Winning developer adoption is essential to Google’s broader goal of turning Gemini into a revenue-generating platform that powers AI-driven products and services across industries. Why Developers Want AI in the Terminal Why Developers Want AI in the Terminal The terminal remains an important workspace for developers working on everything from web apps to infrastructure automation. It is where they compile code, run tests, deploy builds, and manage cloud resources. Putting Gemini AI directly inside the terminal addresses a growing expectation: AI should meet developers where they are, without forcing them into new, unfamiliar interfaces. Gemini CLI is designed to help developers perform real coding tasks faster. That includes generating code snippets, troubleshooting errors, automating repetitive shell commands, and assisting with deployment scripts. Early users have reported that Gemini CLI can help reduce context switching and speed up problem-solving, though feedback on reliability and output quality remains mixed. The Rise of Agentic AI in Developer Workflows The Rise of Agentic AI in Developer Workflows Gemini CLI also arrives at a time when AI development tools across the industry are moving beyond passive assistants. There is growing interest in agentic AI (AI capable of reasoning through multi-step tasks and taking actions with limited human input). Rather than simply suggesting code, many of these emerging tools are starting to execute full workflows. For Gemini CLI, this opens the door to future features where developers might ask AI to set up an entire environment, refactor a section of code, or even run deployment pipelines autonomously. Competitors like Cognition Labs with Devin and Microsoft with its AutoDev research are already experimenting with autonomous AI agents for software development. The launch of Gemini CLI shows that Google wants to influence the uptake of AI. While Gemini CLI is newly launched and still evolving, it is already positioned as an open-source AI agent capable of planning and executing multi-step developer tasks. For Google, succeeding in this space is about making Gemini indispensable to the AI-driven software development pipelines that businesses will rely on going forward. Addressing Trust and AI Output Quality Addressing Trust and AI Output Quality Developers remain cautious about using AI-generated code in production environments. Concerns about security vulnerabilities, coding errors, and hallucinated outputs are common. For Google to gain traction with Gemini CLI, it will need to demonstrate that its AI outputs are reliable, accurate, and safe to use at scale. Google has stated that Gemini models are trained with quality and safety in mind, using grounding techniques and reinforcement learning with human feedback to improve performance on coding-related tasks. Still, early reviews of Gemini CLI (like this one) suggest that output quality is inconsistent, especially for more complex coding queries. Google will need to address these concerns quickly if it wants developers to trust Gemini CLI for anything beyond basic coding help. like this one like this one Why Open Source Matters for Adoption Why Open Source Matters for Adoption Google’s decision to release Gemini CLI as open source is an important part of its developer strategy. Open source projects tend to build faster trust within developer communities by offering transparency, extensibility, and the opportunity for community contributions. Google has a track record of growing developer adoption through open source tools, with TensorFlow and Kubernetes being two notable examples. Making Gemini CLI open source helps reduce concerns about vendor lock-in and allows developers to audit the code, suggest improvements, and tailor the tool to their own workflows. This open approach could help differentiate Gemini CLI from more closed alternatives like GitHub Copilot CLI or proprietary coding assistants from other AI labs. The Competitive Landscape for AI Coding Tools The Competitive Landscape for AI Coding Tools The market for AI development tools is becoming crowded and highly competitive. GitHub Copilot has become a leading tool in the integrated development environment (IDE) space, offering integration with Visual Studio Code and other popular development environments. Its widespread adoption and tight integration with these platforms underscore its prominent position among AI-powered coding assistants OpenAI’s ChatGPT, especially with the introduction of code interpreter functionality in GPT-4o, has become an alternative for developers working in browser-based environments. Anthropic’s Claude models are gaining adoption among teams that prioritize safety and grounded outputs. Gemini CLI enters this landscape with a distinct focus on terminal-based workflows and open-source accessibility. That gives Google an entry point with developers who prefer command-line tools and who value flexibility and customization in how they integrate AI into their development processes. Where Gemini CLI Fits in the AI Developer Ecosystem Where Gemini CLI Fits in the AI Developer Ecosystem AI tools for developers now span multiple environments: chatbots, integrated development environment plugins, web-based coding platforms, and command-line interfaces. Each plays a distinct role in how developers build, test, and deploy software. Chat-based tools support exploratory coding and general problem-solving. IDE plugins offer real-time code completion and inline assistance. CLIs have become essential for infrastructure management, DevOps automation, and rapid, context-aware code execution. Gemini CLI allows Google to extend Gemini’s reach across this full toolchain. Rather than limiting Gemini to chat interfaces or cloud APIs, Google is now positioning its models to support developers at multiple points in the software development lifecycle. That broader coverage matters strategically. The more environments where Gemini can assist with coding and deployment, the more likely it becomes that businesses will treat Google’s models as an integral part of their AI development workflows. The Stakes for Google The Stakes for Google Gemini CLI is just one product, but it underlines something larger about Google’s business strategy in AI. To compete for enterprise adoption and long-term platform relevance, Google needs more than research breakthroughs and model performance benchmarks. It needs to turn Gemini into something developers rely on daily and that businesses build into their own products and services. Extending Gemini into the terminal means that Google is taking a necessary step toward that goal. The next challenge is turning initial adoption into sustained, ecosystem-wide integration, which will determine how much of the enterprise AI market Google can capture.

Gemini CLI Is Google’s Quietest Power Move Yet

Gemini CLI е най-тихият Power Move на Google

Gemini CLI és el moviment de potència més silenciós de Google

Gemini CLI er Googles stilleeste Power Move nogensinde

Το Gemini CLI είναι το πιο ήσυχο Power Move της Google

Gemini CLI es el movimiento de energía más silencioso de Google

Gemini CLIは、Googleの最も静かなパワーモーブです。

«Gemini CLI» – «Google» ең үздік Power Move

Gemini CLI е најтишиот Power Move на Google

Gemini CLI нь Google-ийн хамгийн хялбар эрчим хүчний хөдөлгөөн юм

Gemini CLI دی د Google تر ټولو ساکت قدرت حرکت

Gemini CLI اب تک گوگل کی سب سے ساکت طاقت کی حرکت ہے

It’s 2025, and somehow, despite Google's near-omniscient algorithms and AI prowess, my Gmail inbox still looks like a dumping ground for third-rate spam from so-called “SEO experts” and “web development companies,” mostly based in India. The annoying and unsolicited emails flood inboxes every single day, each one a slight variation of the last: bad grammar, fake names like “Jennifer Smith” or “Alex Brown,” and generic, borderline deceptive promises like “guaranteed top ranking on Google in 10 days” or “expert WordPress redesigns for just $199.” It’s relentless, shameless, and absolutely maddening. emails flood inboxes fake names And here's the kicker: Gmail knows. Their AI can tell the difference between spam and legitimate communication with terrifying precision when it wants to. Yet somehow, these spammy “Hi Sir/Madam” cold pitches from random Gmail addresses (often @gmail.com or .in domains) keep slipping through the filters and into our inboxes. knows spam The messages follow a predictable format—mass-blasted, unsolicited, and often masked under the guise of “business opportunities.” Make no mistake: these are not just annoying; they are predatory marketing ploys designed to scam small business owners and freelancers who may not know better. Let’s be brutally honest here: this is an industry, not just a few bad apples. There's an entire shadow economy of digital marketing mills, lead generation farms, and so-called SEO “agencies” that operate in high-volume, low-quality models. industry They purchase email lists, scrape LinkedIn, or use shady data vendors to get leads, then spam indiscriminately. It’s digital pollution, and much of it is rooted in poorly regulated outsourcing hubs in India, where enforcement is practically nonexistent, and accountability is an afterthought. You might say, "Just mark it as spam." I have. Hundreds of times. And Gmail's spam filter does catch a lot, but not enough. These operators have gotten smart—they rotate email accounts, subtly change their wording, and sometimes even attempt follow-ups. enough They evade spam filters the same way malware evades antivirus software: constantly evolving. But here's where Google is complicit—because it allows it. Gmail still lets people send mass emails from personal Gmail accounts. There’s no throttle, no vetting, no authentication process when someone opens a Gmail account with the sole purpose of blasting thousands of junk SEO offers for distributed fake accounts because it allows it This isn't about targeting one country unfairly. This is about the disproportionate volume of spam originating from specific known sources—often clustered in cities like Noida, Delhi, or Ahmedabad. specific known sources It’s not xenophobic to call out a problem that’s geographically concentrated and structurally exploited. These entities hide behind VPNs, fake names, and burner accounts, and Google does nothing but twiddle its thumbs while real users waste hours deleting garbage and trying not to fall victim to scams. Google has the data. They have the AI. They own the infrastructure. They could put a stop to this if they wanted to. They could implement aggressive outbound spam detection. They could rate-limit personal Gmail accounts that send too many cold emails. could They could apply stricter monitoring of new accounts exhibiting mass-mailing behavior. But they don’t. Why? Because spam like this doesn’t really hurt them. In fact, some of it drives people toward paid Google Workspace accounts or filters that promise better management features. Meanwhile, the rest of us are stuck hitting “report spam” like it's a full-time job. them At this point, it’s negligence. And worse, it erodes trust. Gmail used to be the gold standard of email services. But if it continues to allow its platform to be weaponized by shady overseas lead farms peddling fake SEO and half-baked web development, it’s going to lose that edge. Because once spam becomes indistinguishable from legitimate email, your inbox becomes useless. And It's Not Just Gmail — Outlook Is a Spam Sewer Too And It's Not Just Gmail — Outlook Is a Spam Sewer Too As much as Gmail deserves the heat, let’s not pretend Outlook is innocent here. If Gmail is the front door spammers are walking through, Outlook is the back window they’re crawling into. These same shady SEO and web development peddlers have taken to creating free Outlook, Hotmail, and Live.com addresses to bypass Gmail’s increasingly decent (though still flawed) spam detection. And what’s worse? Outlook’s spam filters are even less reliable. less It’s the same pattern: an email arrives from a sketchy-looking Outlook address like seoexpert2023@outlook.com or websolutionsindia@live.com, with a subject line like “Improve Your Google Ranking” or “Website Redesign Proposal.” seoexpert2023@outlook.com websolutionsindia@live.com The body of the email is the same template garbage—broken English, absurd claims, and fake names—and somehow, it lands right in your inbox. Why? Because Microsoft’s Outlook spam filtering is stuck in 2010. It's slow to learn, easy to manipulate, and barely flags these templated garbage messages as suspicious. And just like Gmail, Outlook allows these free accounts to be spun up in bulk with very little friction. No real identity verification, no email send limits that matter, no proactive enforcement. These platforms are being weaponized by spam factories, and the tech giants hosting them are still acting like spam is just a "cost of doing business" rather than a quality of service issue. quality of service We’re not asking for miracles—we’re asking the two biggest email providers on the planet to stop being passive hosts to spam operations run from digital sweatshops. Gmail and Outlook both have the resources and the AI capability to end this flood of junk. The only thing missing is the will. Google, Microsoft, it’s time. No more excuses. No more turning a blind eye. Start cracking down on this flood of SEO and web dev spam originating from Gmail accounts. Your users are tired of wading through it. The tools exist. You have the power. Do the right thing—for your platform, your users, and the integrity of online communication.

Google (gmail.com) Must Crack Down on SEO Spam Emails From Lead Gen Farms In India

Today, we witness how the era of generative AI is reshaping the way we search for information. Where we once fired off Google searches without a second thought, AI has now picked up the baton, helping people to find necessary information. But the topic is more nuanced than it may seem at first glance. Today, we witness how the era of generative AI is reshaping the way we search for information. Where we once fired off Google searches without a second thought, AI has now picked up the baton, helping people to find necessary information. But the topic is more nuanced than it may seem at first glance. On the one hand, a recent survey shows that 55% of people prefer using generative AI tools over traditional search engines. On the other hand, according to recent data, Google Search is 373 times bigger than ChatGPT search, highlighting that, despite the rise of AI, traditional search engines continue dominating. 55% 55% 373 373 So, is AI really the killer of traditional searching — or does it just complement it? Let’s dig into details, explore how both AI and search engines operate, and take a closer look at the strengths and shortcomings of generative AI. The Ways Machines Think: Google vs. AI It is important to first define key differences in the algorithms behind traditional search engines — with Google as one of the most prominent players — and generative AI. These two have fundamentally different technologies under the hood. Search engines like Google were developed decades ago when the technological boom was only gaining momentum. They were designed with a clear purpose: to find existing information on the web. They are not supposed to generate information — instead, they scan a massive index of the internet, sort through billions of web pages, and rank them based on authority, relevance, and other signals. So, the system is optimized for retrieval and built to guide you toward the sources. At their core, search engines rely on algorithms designed for ranking and indexing. For example, when you search for “the cheapest hotel in Miami,” the algorithm scans pages, indexing those with relevant keywords such as “cheapest hotel,” “Miami,” and “reviews.” Such factors as the credibility of the source (e.g., big hotel/booking aggregators), frequency of keyword appearance, and the quality of the overall content are ranked by the search engine to provide you with the most relevant results. Conversely, generative AI models are powered by large language models (LLMs) and are designed not to retrieve content but to generate it. Their core function is to predict the next word in a sequence, paying attention to patterns from vast training datasets, which include books, websites, code, and more. As a result, they provide human-like, conversational responses that are context-aware. Unlike search engines, which rely on ranking and indexing, generative AI models rely on probability and language modelling. Even when connected to real-time data through retrieval-augmented generation (RAG) systems, their output remains constructive — reflecting what they have absorbed without direct quotation from the source. Say you are curious about how to make up a perfect resume. In that case, AI could pull data from various HR guides, stories, or even advice from experts to generate a custom list of “dos” and “don’ts” for you. However, factual consistency is where AI typically stumbles. But this is what I will talk about later. Generally speaking, search engines lead you to the answers — generative AI builds them for you. Understanding this core difference is key to making the most of both — and now, let’s break down where AI truly excels over traditional search engines and where it falls short. Search Smarter, Not Harder? The Trade-offs of Generative AI At first glance, it might seem that AI is ready to replace conventional search bars — but is that really the case? This definitely calls for a deeper dive into the pitfalls and strengths of this cutting-edge technology, which could seem almost impeccable. Unarguably, when it comes to efficiency, generative AI models are more advantageous. They are not only faster than traditional search engines but also deliver comprehensive and context-aware answers — all in one go. This results in growing user satisfaction: 20% of consumers cite the speed, while 25% favor the AI for relevant search results. So, people simply do not need to sift through tons of links, as they get tailored responses to their requests almost immediately. growing growing Still, the benefits do not come without caveats, do they? While AI may feel smarter and faster than traditional search engines, it can occasionally manipulate facts, miss recent updates, or offer too generalized data — a phenomenon called “AI hallucination.” Plus, unlike Google, it does not show where the information comes from during the initial request, making users experience hurdles when trying to verify it. So, when accuracy is critical, many users turn to their old friends — search engines. called called A Rivalry or a Dynamic Duo? As it is becoming clear, AI offers undeniable advantages, but it is not without flaws. And this brings us to a crucial point: AI could be a great co-pilot, but it is not yet a full replacement. This is confirmed by the fact that 99% of people who use AI for searching purposes continue utilizing traditional search engines. 99% 99% In fact, AI, with its development by leaps and bounds, has yet to reach the point where it can fully replace Google or other search engines. One day, when AI is completely integrated into our online experiences, the act of “Googling” may feel like a voice from the past. However, for now, it is just a partnership rather than a competition.

Google Is Dead: Could AI Bury Traditional Searching?

Google just dropped a bombshell on the tech world by acquiring cloud security startup Wiz for a staggering $32 billion in cash. The deal marks one of the largest cybersecurity acquisitions ever, and it's raising eyebrows across the world.While Google is framing this as a security powerplay for its cloud division, I'm not convinced this massive bet will pay off. Here's why this might be Google's most expensive mistake. A price tag that defies gravity Let's put this in perspective. Google is paying $32 billion for a company founded just four years ago in 2020. Wiz was valued at $12 billion after raising $1 billion last spring. That means Google is paying nearly triple Wiz's last valuation, and approximately 10% of Alphabet's entire cash reserves ($95.7 billion) for this single acquisition. Even more telling? Google reportedly tried to buy Wiz about six months ago for $23 billion, but the deal fell through due to investor and antitrust concerns. Now they're back, paying an additional $9 billion. That's a 39% premium in half a year for essentially the same company. Someone at Google really, really wants Wiz. The multi-cloud conundrum Google claims Wiz will continue supporting Amazon Web Services, Microsoft Azure, and Oracle Cloud. Sounds good on paper, but ask yourself: is Google really motivated to make its expensive new security tool work flawlessly on competing platforms? The reality is that Google Cloud remains a distant third in the cloud race behind AWS and Azure. This acquisition seems like a desperate attempt to gain leverage rather than a coordinated security strategy. Google is essentially trying to become the security layer for its competitors' infrastructure. That's a precarious position that creates misaligned incentives from day one. Security sells, but who's buying? Wiz has undoubtedly built an impressive AI-driven security platform that helps organizations identify vulnerabilities across their cloud infrastructures. But is advanced cloud security enough to shift enterprise spending patterns or cloud provider preferences? Also, only 44% of middle-market firms have invested in cybersecurity defenses. Despite all the high-profile breaches and constant warnings, most organizations still view security as an unnecessary evil rather than a competitive advantage. Will enterprise customers suddenly pay premium prices for Google-owned Wiz when countless other security vendors exist? The antitrust shadow Despite the assertion that Trump's administration has created a "more deal-friendly antitrust environment," large tech acquisitions still face intense regulatory scrutiny. The Wiz deal will undoubtedly trigger reviews, potentially delaying integration and creating uncertainty among customers and employees. This regulatory scrutiny isn't just a temporary inconvenience. It could fundamentally alter how Google can leverage its new acquisition, potentially limiting the very synergies that justified the massive price tag in the first place. The talent retention challenge Cybersecurity experts are among the most sought-after professionals in tech. Wiz's founding team previously built and sold Adallom to Microsoft for $320 million in 2015. Now they've created a company that's selling for 100 times that amount just a decade later. These are exceptional entrepreneurs with proven track records. But will they stick around after the acquisition? Google's corporate culture and bureaucracy are drastically different from a fast-moving startup environment. Once the founders and key technical talent collect their acquisition payouts, what incentive do they have to stay? The history of tech acquisitions suggests many will leave to start new ventures, taking crucial institutional knowledge with them. The bottom line Google's $32 billion gamble on Wiz represents either remarkable foresight or an expensive miscalculation. While cybersecurity remains critically important, the price tag, integration challenges, and competitive dynamics all suggest this acquisition may not deliver the value Google expects. For a company that built its empire on organic growth and smaller, strategic acquisitions, this massive bet on Wiz stands out as an anomaly. Only time will tell if Google's cloud security gambit pays off or joins the long list of big tech's expensive mistakes.

Has Google Made a $32 Billion Cloud Security Blunder?

Google 32 milyard dollarlıq bulud təhlükəsizliyi səhvi etdi?

Направил ли е Google грешка в облачната сигурност за 32 милиарда долара?

Da li je Google napravio sigurnosnu grešku od 32 milijarde dolara u oblaku?

Hat Google einen Cloud-Sicherheitsfehler im Wert von 32 Milliarden Dollar begangen?

Η Google έκανε μια γκάφα 32 δισεκατομμυρίων δολαρίων στο Cloud Security;

¿Ha cometido Google un error de seguridad en la nube de 32 mil millones de dólares?

Google は 320 億ドルのクラウド セキュリティの失策を犯したのか?

Nanao fahadisoana $32 Miliara Cloud Security ve i Google?

के गुगलले ३२ अर्ब डलरको क्लाउड सुरक्षा गल्ती गरेको छ?

Czy Google popełniło błąd w zakresie bezpieczeństwa chmury wart 32 miliardy dolarów?

Je, Google Imetengeneza Blunder ya Usalama wa Wingu ya $32 Bilioni?

Google có phạm sai lầm về bảo mật đám mây trị giá 32 tỷ đô la không?

How can blockchain handle complex AI computations without losing its core promise of transparency? The Flare x Google Cloud Hackathon, held from March 7-9, 2025, at UC Berkeley’s California Memorial Stadium, tackled this question head-on. Over 460 developers and researchers from institutions like UC Berkeley, the University of Waterloo, and ETH Zurich participated, showcasing how blockchain and AI can integrate using verifiable off-chain computation. The Flare x Google Cloud Hackathon, held from March 7-9 in collaboration with Blockchain at Berkeley, demonstrated how verifiable AI can be seamlessly integrated with blockchain technology. Flare Blockchain at Berkeley Blockchain at Berkeley Addressing Blockchain’s Computational Limitations Blockchain excels at decentralized consensus but falters with the heavy data processing AI demands. The event introduced a solution: Google Cloud’s Confidential Space, built on Trusted Execution Environments (TEEs). TEEs process complex tasks off-chain in secure hardware enclaves, producing cryptographic attestations verified on Flare’s blockchain. This ensures computations remain tamper-proof. Flare’s built-in protocols, the Flare Time Series Oracle (FTSO) and Flare Data Connector (FDC), provided data integrity and provenance, critical for AI applications. Further, one of the key challenges in blockchain technology is achieving rich data computation while maintaining transparency and security. Traditional blockchains excel at decentralized consensus and deterministic execution but struggle with large-scale parallel processing, particularly for AI-intensive workloads. This hackathon sought to overcome that limitation by leveraging Google Cloud Confidential Space, a secure enclave built on Trusted Execution Environments (TEEs). Confidential Space Confidential Space Confidential Space ensures hardware-enforced confidentiality and generates cryptographic attestations, which can be verified on the Flare blockchain. This process guarantees that computations occur in a tamper-proof environment, preserving both data integrity and security. Flare’s enshrined data protocols, such as the Flare Time Series Oracle (FTSO) and the Flare Data Connector (FDC), played a crucial role in ensuring data provenance and integrity verification for AI applications. Flare Time Series Oracle Flare Time Series Oracle A Competitive and Innovative Hackathon With over 460 participants competing across four tracks, the hackathon produced verifiable AI solutions ranging from AI-powered decentralized finance (DeFi) applications (DeFAI) to consensus learning models. Every project utilized Confidential Space instances running on AMD’s Secure Encrypted Virtualization (SEV) platform with virtual Trusted Platform Module (vTPM) attestations. These attestations provided cryptographic proof that all AI computations were executed within an isolated, trusted environment. Rene Kolga, Product Manager at Google Cloud, expressed enthusiasm about the developers' engagement with the Confidential Space secure enclaves, stating: “We're thrilled to see developers using our Confidential Space secure enclaves to build trusted AI solutions. Projects like 2DeFi and the Flare AI Kit’s launch are exciting steps towards a future where AI and blockchain ensure data integrity and computational assurance.” 2DeFi: Bridging Traditional Finance and DeFi with AI One of the outstanding projects from the hackathon was 2DeFi, an AI-powered solution developed by University of Waterloo students Alex and Hitarth. The project won first place in the AI x DeFi (DeFAI) track and secured second place in the RAG Knowledge track. 2DeFi 2DeFi 2DeFi aimed to simplify the transition from traditional finance (TradFi) to decentralized finance (DeFi) by integrating Google Gemini AI. Users could upload screenshots of their Robinhood portfolios, which Gemini 2.0 then analyzed to assess risk tolerance. The AI-generated risk profile was mapped to an automated DeFi strategy, incorporating staking and liquidity provision on Flare. To streamline onboarding, 2DeFi also introduced embedded wallets, allowing users to create Google login-based wallets on Flare, removing the complexities of traditional Web3 user experiences. Flare AI Kit: Empowering Verifiable AI on Blockchain The hackathon also marked the official kickoff of Flare AI Kit, an open-source software development kit (SDK) designed for building verifiable AI agents on Flare. The kit leverages Google Cloud Confidential Space to provide developers with secure, attestable AI execution environments, ensuring AI safety, provenance, and verifiability. Flare AI Kit Flare AI Kit Hackathon participants demonstrated the potential of Flare AI Kit as a foundation framework for AI-powered blockchain applications. Moving forward, Flare AI Kit is expected to evolve into a production-ready framework, further enhancing functionality, usability, and integration options. The ultimate goal is to make Flare AI Kit available on the Google Cloud Marketplace, where enterprises and developers can access it as a turnkey solution. The Future of Verifiable AI on Blockchain The success of the Flare x Google Cloud Hackathon is just the beginning. As developers and researchers continue to push the boundaries of AI and blockchain convergence, projects like Flare AI Kit will play a crucial role in shaping the future of verifiable AI applications. By integrating Confidential Space TEEs, AI, and the Flare blockchain, Flare AI Kit is set to redefine how secure, verifiable AI applications are built, deployed, and trusted globally. Developers looking to get started can explore the Flare Developer Hub for in-depth documentation and resources. Flare Developer Hub Flare Developer Hub Don’t forget to like and share the story!

Can Blockchain and AI Finally Trust Each Other? Flare and Google Cloud’s Hackathon Says Yes

Blockchain እና AI በመጨረሻ እርስ በርስ መተማመን ይችላሉ? Flare እና Google Cloud's Hackathon አዎ ይላል።

Mogu li Blockchain i AI konačno vjerovati jedni drugima? Hackathon kompanije Flare i Google Cloud kaže da

Mohou si blockchain a AI konečně věřit? Flare a Hackathon Google Cloud říkají Ano

¿Pueden finalmente la blockchain y la IA confiar entre sí? El hackatón de Flare y Google Cloud afirma que sí.

آیا بلاک چین و هوش مصنوعی در نهایت می توانند به یکدیگر اعتماد کنند؟ Flare و Google Cloud's Hackathon بله می گوید

Կարո՞ղ են բլոկչեյնը և AI-ն վերջապես վստահել միմյանց: Flare-ը և Google Cloud's Hackathon-ն ասում է այո

ブロックチェーンと AI はついに信頼できるのか？Flare と Google Cloud のハッカソンで「イエス」と判定

Блокчейн мен AI бір-біріне сене ала ма? Flare және Google Cloud хакатоны «Иә» дейді

Czy Blockchain i AI w końcu mogą sobie zaufać? Hackathon Flare i Google Cloud mówi „tak”

Blockchain மற்றும் AI இறுதியாக ஒன்றையொன்று நம்ப முடியுமா? Flare மற்றும் Google Cloud இன் Hackathon ஆம் என்று கூறுகிறது.

ในที่สุด Blockchain และ AI จะสามารถไว้วางใจซึ่งกันและกันได้หรือไม่? Flare และ Hackathon ของ Google Cloud บอกว่าใช่

Чи можуть Blockchain і AI нарешті довіряти один одному? Хакатон від Flare і Google Cloud каже «так».

Google AI Studio Tutorial for Beginners

Apple Asks Court to Pause Proceedings So It Can Join Google in US Government Antitrust Case

Hello JavaScript Enthusiasts! The holiday season may be in full swing, but the JavaScript world isn’t taking a break. We’ve got some game-changing updates, tools, and releases that will supercharge your workflow, whether you're fine-tuning performance, diving into modern frameworks, or exploring new databases. Project IDX From Google Google has introduced Project IDX, which aims to eliminate the need for local environments—everything happens directly in your browser. Whether you’re starting a fresh project or importing an existing one, you can hit the ground running with support for popular frameworks like Angular, NextJS, and more. Highlights include: Gemini AI Assistant: Code faster and smarter with real-time AI-powered suggestions.
Live Previews & Emulators: Test your work directly within the browser, skipping the hassle of setting up external tools.
Effortless Collaboration: Share projects as easily as you would a Google Doc, making team development seamless.
Full Android Studio Integration: Build and preview native Android apps without ever leaving your browser.
Templates for Popular Technologies: Kickstart your project with templates for React, Svelte, and the Gemini API.
One-Click Deployment: Seamless deployment to Firebase or Cloud Run. Project IDX is a game-changer for simplifying development and fostering collaboration! Base UI 1.0 by Material UI Team The Material UI team has released Base UI 1.0, an unstyled React component library designed for ultimate flexibility. This new version is perfect for developers looking to craft bespoke designs without predefined styling constraints. Customization: Use Tailwind, CSS-in-JS, or plain CSS—it adapts to whatever fits your style. Accessibility-First: While unstyled, it still ensures components meet high accessibility standards. Base UI 1.0 gives you the freedom to build exactly what you want while maintaining a focus on clean and accessible design. Tools & Releases YOU Should Know About Now, let’s take a quick look at the latest tools and updates that can boost your workflow: Vector.dev: Logs can be chaotic, but Vector.dev makes them manageable by converting unstructured logs into clean JSON logs. This tool simplifies filtering, searching, and dashboard creation, making it a must-have in production environments. Ghostty Terminal Emulator: Meet Ghostty, the sleek terminal emulator for macOS and Linux. With features like Kitty graphics, native tabs, and lightning-fast performance, Ghostty makes your terminal experience feel intuitive and responsive. DiceDB: DiceDB is an open-source caching database under AGPL 3.0 designed to store and retrieve data efficiently, making your apps faster and more scalable. Inertia 2.0: For Laravel fans, Inertia 2.0 makes integrating Laravel with frontend frameworks like React, Vue, or Svelte smoother than ever. With async requests, prefetching, and real-time polling, you can expect faster load times and a seamless navigation experience. Apollo Client 3.12: For those using GraphQL, Apollo Client 3.12 introduces data masking, ensuring that components only access the data they need. This boosts performance and reduces bugs, especially when working with TypeScript. Cline 3.0: Last but not least, Cline 3.0 is revolutionizing how we approach coding projects. It’s fully autonomous, handling command approvals, tool management, and even browser navigation—no input required. It’s integrated with Visual Studio Code and completely free. And that wraps up this issue of This Week In JavaScript! Thank you for tuning in! As the holiday season approaches, we hope you get a chance to unwind, maybe work on some personal projects, and enjoy some festive downtime. Be sure to share this newsletter with your fellow developers and subscribe to get the latest updates directly in your inbox. Until next time, happy coding, and happy holidays! Hello JavaScript Enthusiasts! The holiday season may be in full swing, but the JavaScript world isn’t taking a break. We’ve got some game-changing updates, tools, and releases that will supercharge your workflow, whether you're fine-tuning performance, diving into modern frameworks, or exploring new databases. Project IDX From Google Project IDX From Google Google has introduced Project IDX , which aims to eliminate the need for local environments—everything happens directly in your browser. Project IDX Whether you’re starting a fresh project or importing an existing one, you can hit the ground running with support for popular frameworks like Angular, NextJS, and more. Highlights include: Gemini AI Assistant: Code faster and smarter with real-time AI-powered suggestions. Live Previews & Emulators: Test your work directly within the browser, skipping the hassle of setting up external tools. Effortless Collaboration: Share projects as easily as you would a Google Doc, making team development seamless. Full Android Studio Integration: Build and preview native Android apps without ever leaving your browser. Templates for Popular Technologies: Kickstart your project with templates for React, Svelte, and the Gemini API. One-Click Deployment: Seamless deployment to Firebase or Cloud Run. Gemini AI Assistant: Code faster and smarter with real-time AI-powered suggestions. Gemini AI Assistant: Live Previews & Emulators: Test your work directly within the browser, skipping the hassle of setting up external tools. Live Previews & Emulators: Effortless Collaboration: Share projects as easily as you would a Google Doc, making team development seamless. Effortless Collaboration: Full Android Studio Integration: Build and preview native Android apps without ever leaving your browser. Full Android Studio Integration: Templates for Popular Technologies: Kickstart your project with templates for React, Svelte, and the Gemini API. Templates for Popular Technologies: One-Click Deployment: Seamless deployment to Firebase or Cloud Run. One-Click Deployment: Project IDX is a game-changer for simplifying development and fostering collaboration! Base UI 1.0 by Material UI Team Base UI 1.0 by Material UI Team The Material UI team has released Base UI 1.0 , an unstyled React component library designed for ultimate flexibility. This new version is perfect for developers looking to craft bespoke designs without predefined styling constraints. Material UI Base UI 1.0 React component library Customization: Use Tailwind, CSS-in-JS, or plain CSS—it adapts to whatever fits your style. Customization: Use Tailwind, CSS-in-JS, or plain CSS—it adapts to whatever fits your style. Customization: Accessibility-First: While unstyled, it still ensures components meet high accessibility standards. Accessibility-First: While unstyled, it still ensures components meet high accessibility standards. Accessibility-First: Base UI 1.0 gives you the freedom to build exactly what you want while maintaining a focus on clean and accessible design. Tools & Releases YOU Should Know About Tools & Releases YOU Should Know About Now, let’s take a quick look at the latest tools and updates that can boost your workflow: Vector.dev: Logs can be chaotic, but Vector.dev makes them manageable by converting unstructured logs into clean JSON logs. This tool simplifies filtering, searching, and dashboard creation, making it a must-have in production environments. Vector.dev: Logs can be chaotic, but Vector.dev makes them manageable by converting unstructured logs into clean JSON logs. This tool simplifies filtering, searching, and dashboard creation, making it a must-have in production environments. Vector.dev: Ghostty Terminal Emulator: Meet Ghostty, the sleek terminal emulator for macOS and Linux. With features like Kitty graphics, native tabs, and lightning-fast performance, Ghostty makes your terminal experience feel intuitive and responsive. Ghostty Terminal Emulator: Meet Ghostty, the sleek terminal emulator for macOS and Linux. With features like Kitty graphics, native tabs, and lightning-fast performance, Ghostty makes your terminal experience feel intuitive and responsive. Ghostty Terminal Emulator: DiceDB: DiceDB is an open-source caching database under AGPL 3.0 designed to store and retrieve data efficiently, making your apps faster and more scalable. DiceDB: DiceDB is an open-source caching database under AGPL 3.0 designed to store and retrieve data efficiently, making your apps faster and more scalable. DiceDB: Inertia 2.0: For Laravel fans, Inertia 2.0 makes integrating Laravel with frontend frameworks like React, Vue, or Svelte smoother than ever. With async requests, prefetching, and real-time polling, you can expect faster load times and a seamless navigation experience. Inertia 2.0: For Laravel fans, Inertia 2.0 makes integrating Laravel with frontend frameworks like React, Vue, or Svelte smoother than ever. With async requests, prefetching, and real-time polling, you can expect faster load times and a seamless navigation experience. Inertia 2.0: Apollo Client 3.12: For those using GraphQL, Apollo Client 3.12 introduces data masking, ensuring that components only access the data they need. This boosts performance and reduces bugs, especially when working with TypeScript. Apollo Client 3.12: For those using GraphQL, Apollo Client 3.12 introduces data masking, ensuring that components only access the data they need. This boosts performance and reduces bugs, especially when working with TypeScript. Apollo Client 3.12: Cline 3.0: Last but not least, Cline 3.0 is revolutionizing how we approach coding projects. It’s fully autonomous, handling command approvals, tool management, and even browser navigation—no input required. It’s integrated with Visual Studio Code and completely free. Cline 3.0: Last but not least, Cline 3.0 is revolutionizing how we approach coding projects. It’s fully autonomous, handling command approvals, tool management, and even browser navigation—no input required. It’s integrated with Visual Studio Code and completely free. Cline 3.0: Last but not least, Cline 3.0 is revolutionizing how we approach coding projects. It’s fully autonomous, handling command approvals, tool management, and even browser navigation—no input required. It’s integrated with Visual Studio Code and completely free. Cline 3.0: And that wraps up this issue of This Week In JavaScript! Thank you for tuning in! As the holiday season approaches, we hope you get a chance to unwind, maybe work on some personal projects, and enjoy some festive downtime. Be sure to share this newsletter with your fellow developers and subscribe to get the latest updates directly in your inbox. Until next time, happy coding, and happy holidays!

Stories, News & Mentions about GOOGLE

Trending Topics

Classic

Neon Noir

Minty

Newspaper

HN StartUps