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Technology

Google brings Gemini 3.7 Flash for coding, agents

Google has launched Gemini 3.7 Flash, its latest artificial intelligence model aimed at making software development, coding and AI-agent workflows faster, more accurate and less expensive. The new model, unveiled on August 13, arrives only three weeks after Gemini 3.6 Flash and is positioned as Google’s most capable “workhorse” model so far for coding and agent-based tasks.

The release reflects Google‘s growing focus on AI agents that can do more than simply generate text or answer questions. Gemini 3.7 Flash is designed to handle multi-step tasks, use software tools, work through complex instructions and assist with workflows that previously required substantial human intervention.

Google said the model brings improvements across software engineering, web development and knowledge-intensive work, including areas such as finance, law and biosciences. The company also highlighted better debugging, issue resolution, code generation and instruction-following.

One of the biggest changes is the model’s ability to produce better code on the first attempt. Google said Gemini 3.7 Flash achieved a 43.6% score on the FrontierCode 1.1 Main benchmark, compared with 34.4% for Gemini 3.6 Flash. On DeepSWE v1.1, which measures software-engineering capabilities, the new model scored 65.3%, up from 49% for its predecessor.

For developers, that improvement could mean fewer rounds of prompting, debugging and manual correction. Google said Gemini 3.7 Flash is better at dealing with roadblocks, understanding when clarification is required and following instructions more closely. It also puts more effort into multi-step planning and tool calls, potentially reducing failed attempts when an AI agent is working through a complicated software task.

Web development is another major focus. Google said Gemini 3.7 Flash can create more functional layouts and feature-complete applications with fewer prompts. It can also work from screenshots, images or complete design systems and produce interfaces that more closely follow the original design.

The model recorded an Elo score of 1,588 on Arena.ai’s WebDev Arena, compared with 1,538 for Gemini 3.6 Flash. That improvement is significant for developers using generative AI to create websites and applications, where producing working code is only part of the challenge. Matching the intended user interface and visual design has become equally important.

Google is also pitching Gemini 3.7 Flash as a model for knowledge work and business automation. On the GDP.pdf benchmark for complex document understanding, it scored 34%, compared with 22% for Gemini 3.6 Flash. On AutomationBench, which tests real-world business workflows, the new model achieved 30.4%, compared with 17% previously.

The pricing is another important part of the launch. Google has introduced Gemini 3.7 Flash at $0.75 per million input tokens and $3.75 per million output tokens until the end of 2026. From January 1, 2027, those prices are scheduled to rise to $1.50 per million input tokens and $7.50 per million output tokens.

The lower introductory price is significant because running AI agents can consume large amounts of tokens. Agents often require repeated model calls as they plan tasks, access tools, inspect results and make corrections. Lower inference costs can therefore make autonomous AI systems more practical for businesses and developers operating them at scale.

Gemini 3.7 Flash is available through several Google platforms, including the Gemini API, Google AI Studio, Google Antigravity and Android Studio. Enterprise customers can access it through the Gemini Enterprise Agent Platform and Gemini Enterprise app. The model is also being incorporated into Google’s consumer-facing Gemini Spark service for eligible Google AI Pro and Ultra subscribers.

Gemini Spark, described by Google as a personal AI agent, can use the new model to perform multi-step knowledge-work tasks. Google said the upgrade improves its use of Google Workspace applications, allowing Spark to consolidate files, draft emails and update status documents while working under user direction.

The launch also underlines how quickly the generative AI market is evolving, with technology companies competing across AI models, coding tools and autonomous agents. Google’s three-week gap between Gemini 3.6 Flash and Gemini 3.7 Flash shows the pressure on AI companies to improve models rapidly while keeping inference costs under control.

Google is competing in an increasingly crowded market that includes OpenAI and Anthropic, particularly in coding assistants and autonomous AI workflows. The company is simultaneously developing its premium Gemini models, with its next flagship Pro release still being closely watched by the industry.

Google has also included updated safeguards covering cyber misuse and chemical, biological, radiological and nuclear-related risks. The company said the new model was developed with these protections in mind as it expands the capabilities of AI agents.

With Gemini 3.7 Flash, Google’s message is clear: the next stage of AI competition will not be judged only by how intelligently a model answers a prompt, but by how reliably, affordably and independently it can turn that prompt into completed work.

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Leaders

Google AI veteran Jeff Dean leaves to build startup

Jeff  Dean, Google’s longtime chief scientist and a key architect of its artificial intelligence efforts, has left the company to co-found Discovery Loop, a new AI startup focused on using artificial intelligence to accelerate scientific and engineering breakthroughs.

Dean is not leaving alone. He is joining forces with three other prominent Google AI researchers, Sanjay Ghemawat, Oriol Vinyals and Quoc Le, in a move that brings together some of the industry’s most experienced researchers outside Google’s corporate structure.

Discovery Loop is being established as a public-benefit corporation, with a mission that goes beyond building another consumer AI chatbot. The company wants to use AI to automate parts of the scientific method — allowing systems to generate ideas, design experiments, analyse results and repeatedly test new possibilities.

The ambition is to make scientific discovery faster and more scalable.

Dean’s departure is particularly significant because of his extraordinary influence on Google’s technical foundation. He joined the company in 1999, when Google was still a relatively small organisation, and went on to become one of its most respected engineers and researchers.

Over nearly three decades, he worked on systems that helped Google handle enormous amounts of information and built technologies that became important to the company’s search, computing and AI infrastructure.

He also played a major role in Google’s development of specialised hardware for machine learning, including the Tensor Processing Unit (TPU) programme. TPUs later became a crucial part of Google’s strategy for training and running large AI models.

Dean eventually became Google’s chief scientist, putting him at the centre of the company’s long-term technology strategy.

His move comes at a particularly important moment for Google.

The company is reorganising its AI leadership as competition intensifies across the industry. Google is facing pressure from OpenAI, Anthropic and other AI companies to move quickly in areas ranging from frontier AI models and AI agents to scientific research and coding.

Google DeepMind is also undergoing a leadership reshuffle. Demis Hassabis, who has led DeepMind, is moving away from day-to-day executive responsibilities to focus more heavily on long-term research and become chairman and chief scientist. Koray Kavukcuoglu is taking greater responsibility for AI model development.

Dean’s departure is therefore part of a broader period of change inside Google’s AI organisation.

Yet the creation of Discovery Loop also highlights how the next phase of artificial intelligence may extend beyond the race to build increasingly capable general-purpose models.

The startup wants to focus on what could be called AI for discovery,  systems capable of working through complex scientific problems by repeatedly proposing, testing and refining ideas.

The potential applications are wide. The company is expected to explore areas such as drug discovery, hardware design, engineering and other scientific challenges where progress often depends on running large numbers of experiments.

Traditionally, scientific research can be slow because experiments require time, specialised equipment and human researchers. AI could potentially shorten that cycle by helping researchers identify promising ideas, automate parts of experimental work and analyse huge amounts of data.

Discovery Loop’s founders believe this could create a new model for scientific research, where AI systems operate alongside scientists and engineers rather than simply serving as productivity tools.

The company has also attracted significant backing. Its investors include prominent venture capital firms such as Radical Ventures, Khosla Ventures, Lightspeed, Kleiner Perkins and Doerr Capital. Alphabet, Google’s parent company, is also participating as an investor and cloud partner.

That relationship makes Dean’s exit unusual. While Google is losing a senior AI figure, the company is also backing the new venture and providing cloud infrastructure.

The move reflects the changing relationship between large technology companies and AI startups. Major researchers can now leave established companies with deep technical experience, access to capital and ambitious ideas — while their former employers may still have reasons to support their work.

For Dean personally, the move marks a dramatic change after 27 years at one of the world’s most influential technology companies.

He joined Google during its early growth and remained there through the transformation of search, cloud computing, smartphones, machine learning and generative AI.

Now, instead of helping shape the future from inside Google, he is attempting to build a new organisation around one central question: Can AI dramatically speed up the way humans discover new things?

That question could become increasingly important as artificial intelligence moves from generating content to performing increasingly complex tasks.

Discovery Loop’s success will depend on whether its systems can produce reliable, measurable breakthroughs rather than simply promising faster research.

But with four highly experienced AI researchers at the helm and backing from major technology and venture investors, the startup is already attracting attention.

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1 Minute-Read

EU slaps $1 bn fine on Google again

Google has been fined €1.02 billion (around $1.18 billion) by the European Union for violating the bloc’s Digital Markets Act (DMA), marking one of the biggest penalties imposed under the landmark tech regulation.

EU regulators said the company abused its dominant market position by giving preferential treatment to its own services, undermining fair competition. Google said it disagrees with the decision and plans to challenge the fine.

The ruling adds to the company’s ongoing regulatory challenges in Europe and reinforces the EU’s efforts to curb anti-competitive practices among major technology firms and promote fair digital markets.

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Technology

Google’s Gemini surges to 950 mn monthly users

Google has delivered a strong statement in the global artificial intelligence race, with CEO Sundar Pichai announcing that Gemini now has 950 million monthly active users. The milestone, revealed during Alphabet’s second-quarter 2026 earnings call, underscores how rapidly Google’s AI chatbot has grown and positions it among the world’s most widely used AI platforms.

The announcement comes amid intense competition in generative AI, where companies including OpenAI, Meta and Anthropic are racing to attract users and launch more capable AI models. It also follows comments attributed to Meta’s Chief AI Officer Alexandr Wang, who reportedly questioned Gemini’s popularity. While Pichai did not respond directly, the latest user figures have become Google’s strongest answer to such criticism.

According to Pichai, Gemini’s daily active users have tripled over the past year, reflecting rising adoption among both consumers and businesses. He said Google’s continued investments in AI research, infrastructure and product integration have helped Gemini reach users at an unprecedented pace.

Unlike standalone AI chatbots, Gemini is deeply embedded across Google’s ecosystem. It powers AI features in Search, Gmail, Google Docs, Android, Chrome and Workspace, enabling users to draft emails, summarise documents, answer complex questions, generate code and complete everyday tasks more efficiently. This broad integration has played a key role in accelerating user adoption.

Google has also expanded Gemini’s presence in enterprise software through Google Cloud, where businesses are increasingly using the AI assistant to automate workflows, improve customer service, analyse data and assist software development. As more organisations embrace artificial intelligence, enterprise demand has become an important growth driver for Gemini.

Pichai said Google’s advantage lies in its ability to combine cutting-edge AI models with its own cloud infrastructure, custom-built AI chips and billions of existing users across its products. This “full-stack” strategy allows the company to roll out new AI capabilities at scale while continuously improving performance and reliability.

The strong momentum in AI was reflected in Alphabet’s latest financial results. The company reported robust second-quarter revenue growth, driven by continued strength in Search, Cloud and AI-powered services. Google Cloud emerged as one of the fastest-growing businesses, benefiting from rising enterprise demand for AI infrastructure and generative AI tools.

Gemini’s rapid growth also highlights how the AI landscape has evolved over the past two years. When OpenAI launched ChatGPT, many industry observers believed Google had fallen behind despite years of AI research. Since then, Google has accelerated development of Gemini, introduced more advanced AI models and integrated them across nearly every major product.

The competition, however, remains intense. OpenAI continues to expand ChatGPT’s capabilities, while Meta is investing billions of dollars to strengthen its AI ecosystem. Anthropic and several other AI companies are also introducing increasingly sophisticated models, making innovation and user engagement key battlegrounds.

Rather than focusing only on benchmark scores, technology companies are now measuring success through real-world adoption and everyday usage. In that context, reaching 950 million monthly active users marks a significant achievement for Google and demonstrates that Gemini has become a mainstream AI assistant used across work, education and personal productivity.

Industry experts believe the next phase of competition will depend not only on building smarter AI models but also on making them more useful, accessible and seamlessly integrated into people’s daily lives. Google’s strategy of embedding Gemini across its products appears to be paying off, helping millions of users interact with AI without needing a separate application.

With Gemini now closing in on the one-billion-user milestone, Google has strengthened its position in the global AI race. For Sundar Pichai, the latest figures serve as clear evidence that the company’s long-term investments in artificial intelligence are translating into rapid user growth and expanding influence in one of the technology industry’s most competitive sectors.

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1 Minute-Read

Alphabet profit rises to $28.2 bn in strong quarter

Alphabet, Google’s parent company, reported stronger-than-expected second-quarter results, driven by rapid growth in its cloud business and continued momentum in artificial intelligence (AI).

Revenue rose 14% year-on-year to $103.3 billion, while net profit climbed to $28.2 billion, reflecting healthy demand across its core businesses. Google Cloud posted impressive growth as enterprises increased spending on AI-powered services and cloud infrastructure.

The strong performance also boosted investor confidence in AI-related companies, including Adobe and Broadcom. Alphabet said it will increase capital spending to expand AI infrastructure, signalling its commitment to meeting rising global demand for advanced AI tools and cloud computing services. For more quick updates on corporate earnings and business developments, explore our 1-Minute Read section.

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Uncategorized

Google launches three new Gemini AI models

Google has expanded its Gemini family of artificial intelligence models with the launch of three new versions aimed at developers, businesses and cybersecurity professionals. The company introduced Gemini 3.6 Flash, Gemini 3.5 Flash Lite and Gemini 3.5 Flash Cyber, while also announcing that the release of the much-awaited Gemini 3.5 Pro has been delayed for additional improvements.

The announcement highlights Google’s strategy of building AI models tailored for different user needs instead of offering a single solution for every task. The latest models focus on faster performance, lower operating costs and specialised capabilities that can support businesses deploying AI across multiple sectors.

Leading the new lineup is Gemini 3.6 Flash, Google’s latest high-performance AI model. According to the company, it offers better reasoning, coding, instruction-following and multimodal capabilities while maintaining fast response times. The model is designed to automatically adjust its reasoning depending on the complexity of a prompt, allowing it to respond quickly to simple requests while using additional computing power for more challenging tasks.

Google says this adaptive approach helps developers achieve higher-quality results without significantly increasing costs or slowing down applications. The model is expected to be useful for AI assistants, software development, content creation and enterprise automation.

The company has also launched Gemini 3.5 Flash Lite, which it describes as its most affordable AI model so far. Built for organisations handling large volumes of AI requests, Flash Lite is designed to deliver reliable performance at lower cost.

The model is suitable for everyday business applications such as document summarisation, customer support, language translation, data classification and content generation. By reducing operating expenses, Google hopes the model will appeal to startups and enterprises looking to expand AI adoption without increasing infrastructure costs.

A major addition to the Gemini family is Gemini 3.5 Flash Cyber, a model developed specifically for cybersecurity. Unlike general-purpose AI systems, Flash Cyber has been trained using threat intelligence, vulnerability databases and security research.

The model can assist security teams in analysing malware, identifying vulnerabilities, investigating cyber threats and supporting incident response. Google believes specialised AI will become increasingly important as cyberattacks grow more sophisticated and organisations face greater pressure to strengthen digital security.

The launch reflects growing demand for AI systems that can perform specialised tasks instead of relying only on broad language capabilities. Enterprises are increasingly seeking AI models designed for coding, security, customer service and workflow automation.

While introducing the new Flash models, Google also confirmed that Gemini 3.5 Pro will not be released as originally planned. The company said it requires additional testing to improve reliability and overall performance before making the model publicly available.

Although Google did not announce a revised release date, it said the delay would help ensure a better experience for developers and enterprise customers. The decision comes as AI companies face increasing expectations around model quality, safety and accuracy.

The newly launched models are available through Google AI Studio, the Gemini API and Vertex AI, allowing developers and businesses to integrate them into their applications immediately. This gives organisations access to AI tools for coding, automation, customer engagement, cybersecurity and business operations.

The expansion also reflects the intense competition in the global AI industry, where companies are racing to introduce faster and more capable models. Instead of focusing only on larger AI systems, firms are increasingly developing specialised models that offer better performance for specific business needs.

Google said the new Gemini Flash models are designed to provide a balance between speed, affordability and accuracy, enabling developers to build AI-powered products more efficiently. The company expects the latest releases to support wider AI adoption across industries ranging from technology and finance to healthcare, education and cybersecurity.

With three new Gemini models now available and the Pro version still under development, Google is continuing to broaden its AI ecosystem while focusing on practical applications for developers and enterprise customers.

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Technology

Google changes Play Store rules

Google is set to introduce one of the biggest changes to the Android app ecosystem by allowing third-party app stores to be listed on the Google Play Store from July 22. The move follows a US court ruling in Google’s antitrust case with Epic Games, which accused the tech giant of restricting competition in Android app distribution.

With the new policy, developers of alternative app stores will be able to offer their marketplaces directly through Google Play. This means Android users will have an easier way to discover and install rival app stores without relying on sideloading, a process that often requires downloading apps from external websites and changing device settings.

The change is part of a court order aimed at increasing competition in the Android ecosystem. Although Google is appealing the ruling, it has decided not to seek an emergency stay, allowing the new rules to take effect while the legal process continues.

Epic Games, the maker of Fortnite, welcomed the move, saying it gives developers more freedom and provides users with greater choice over where they download apps. The company has argued that Google’s control over app distribution and in-app payments has limited competition and increased costs for developers.

Google, however, has expressed concerns that allowing rival app stores inside Google Play could expose users to greater security and privacy risks. The company says its Play Store protections help prevent malware, scams and harmful apps, and it plans to continue investing in security measures even after the policy change.

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Leaders

DeepMind chief urges global standards for Frontier AI

Google DeepMind CEO Demis Hassabis has called for the creation of a US-led international body to develop common standards for frontier artificial intelligence, saying global cooperation is essential as AI systems become increasingly powerful.

Speaking at a technology event in Washington, Hassabis said advanced AI is progressing at an extraordinary pace and requires coordinated oversight to ensure it is developed safely and responsibly. He argued that countries should work together instead of creating fragmented regulations that could slow innovation or leave safety gaps.

According to Hassabis, the proposed organisation could play a role similar to international scientific bodies by bringing together governments, researchers and technology companies to establish shared guidelines for developing cutting-edge AI models. He believes common standards would help manage risks while allowing innovation to continue.

His comments come as governments around the world are racing to introduce AI regulations amid rapid advances in generative AI. While many countries have announced national policies, experts have increasingly called for greater international coordination because AI technologies can easily cross borders.

Hassabis also stressed that frontier AI systems have enormous potential to improve healthcare, scientific research, education and productivity. However, he warned that the same technologies could create serious risks if developed without proper safeguards, transparency and accountability.

The DeepMind chief said the United States is well placed to lead such an initiative because of its strong research ecosystem and the presence of many of the world’s leading AI companies. At the same time, he emphasised that any standards body should involve broad international participation to ensure global acceptance.

His remarks reflect growing debate within the technology industry over how best to govern increasingly capable AI models. Companies, policymakers and researchers continue to discuss issues such as safety testing, responsible deployment, transparency and security as AI adoption accelerates.

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Technology

Google launches Gemini Omni, Nano Banana

Google has expanded its artificial intelligence portfolio with the launch of Gemini Omni and Nano Banana 2 Lite, two new AI models designed to make conversations more natural and image creation significantly faster.

The company says Gemini Omni is built to handle voice, video and visual inputs in real time, allowing users to interact with AI more smoothly. The model can understand multiple forms of information simultaneously, enabling quicker and more human-like responses during conversations.

The second launch, Nano Banana 2 Lite, is a lightweight AI model focused on rapid image generation. Google says it can create and edit images from simple text prompts within seconds while using fewer computing resources. The model is intended for developers, businesses and creators looking for fast, high-quality visual content without the need for powerful hardware.

By introducing the new models, Google aims to make AI more accessible across a wide range of applications. From digital assistants and creative tools to educational platforms and business software, the technology is expected to improve productivity and user experience.

Google’s latest offerings place equal emphasis on performance and ease of use, ensuring that AI tools can run efficiently while delivering advanced capabilities.

Developers will be able to integrate both models into applications through Google’s AI ecosystem, opening new possibilities for conversational assistants, image editing, content creation and customer support.

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Technology

Google relaxes Play Store billing

Google is set to roll out one of the biggest changes to its Play Store business model in recent years, giving developers more freedom to choose how payments are processed on Android apps.

The company has expanded its Play Billing Choice programme, allowing eligible app developers to offer alternative payment systems alongside Google’s own billing service. The updated policy takes effect next week and is expected to reduce the fees developers pay for transactions made through external payment providers.

For years, developers have argued that mandatory use of Google’s billing system increased costs and restricted competition. The latest changes are designed to address some of those concerns while still keeping Google Play Billing available as an option for users.

Under the revised programme, developers using alternative payment systems will receive fee reductions compared to standard Play Store commissions. Google says the lower fees reflect the fact that some payment-related services will be handled by third-party providers instead of the company itself.

The policy shift comes amid increasing scrutiny from regulators worldwide. Governments and competition watchdogs have pushed major app store operators to provide more choice and reduce barriers for developers. In response, both Google and other technology giants have gradually adjusted their marketplace rules.

Developers are expected to benefit from greater flexibility and potentially higher earnings. Companies offering subscription services, streaming platforms and digital content could see lower operating costs, allowing them to invest more in product development and customer acquisition.

Google has stressed that security, transparency and consumer protection will remain central to the Play Store experience. Users will continue to see clear payment information regardless of which billing option they choose.

As the new rules come into effect, developers will be watching closely to assess whether lower fees and additional payment choices translate into meaningful business benefits. For the broader app ecosystem, the changes represent another chapter in the ongoing debate over platform control, competition and digital marketplace fairness.

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