Google: We fixed More Chrome Bugs in June Than Over Past 2 Years, Thanks to AI

A general view shows a Google logo on a smartphone screen in front of the European Commission building, Brussels, Belgium, July 23, 2026 (EPA) 
A general view shows a Google logo on a smartphone screen in front of the European Commission building, Brussels, Belgium, July 23, 2026 (EPA) 
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Google: We fixed More Chrome Bugs in June Than Over Past 2 Years, Thanks to AI

A general view shows a Google logo on a smartphone screen in front of the European Commission building, Brussels, Belgium, July 23, 2026 (EPA) 
A general view shows a Google logo on a smartphone screen in front of the European Commission building, Brussels, Belgium, July 23, 2026 (EPA) 

Google, the tech giant, said it has patched more security flaws in its Chrome browser in the last month than in the past two years combined, with help from its internal AI tools.

Google announced that it has fixed a whopping 1,072 security bugs in the last two versions of Chrome, both released in June. That is more than the number of bugs patched in the previous 23 versions released over the last two years, which totaled 1,036 fixes.

Ever since the advent of LLMs, cybersecurity experts have warned that AI-powered systems would find an increasingly and exponentially enormous amount of bugs, forcing defenders to also use AI to get ahead of malicious hackers, according to TechCrunch, a leading online newspaper focused on the technology industry.

It said a chart published by Google, which the company revealed as part of a white paper on the company’s efforts to use AI to find flaws and patch them faster, shows the exponential increase.

“For context, Chrome’s 126 was released in June 2024, while the latest two Chrome releases, Chrome 149 and 150, were released last month,” it said.

Doug Turner, Chrome’s director of engineering, told TechCrunch in a statement that LLMs have “fundamentally shifted the economics of cybersecurity, transforming vulnerability discovery into an automated, industrial-scale operation.”

“By applying models like Gemini, we are preemptively fixing vulnerabilities, outpacing our adversaries and making Chrome safer with every update,” said Turner.

Earlier this month, Microsoft announced that it had patched a record 570 security flaws across its product lines as part of its monthly round of scheduled patches — colloquially known as “Patch Tuesday.” Microsoft cited its own use of AI to explain the sudden jump in bug fixes.

People Limiting AI Use

According to a new report by the Digital Futures Institute at King’s College London (KCL) and Responsible AI UK, people are increasingly choosing to limit or reject the use of AI tools.

The report revealed that 42% of individuals deliberately limit the amount of AI they use, largely due to privacy and security concerns, including some of those who are positive about AI.

“The most common reason chosen for limiting use is concern about data privacy, security and compliance, and the second most common reason is a preference to keep doing work the way it is currently done,” KCL said in a press release.

Taking in over 2,000 people living in the UK, the survey indicated a four percentage point rise to 52% in those who see AI as posing “more risks than benefits” and a drop to 34% of those who take the optimistic opposing view.

At the same time, people appear ever more concerned that there is no leeway to opt out from AI, which many respondents are finding discomforting as they are cornered into using chatbots.

“The majority of people think it would be difficult or impossible for them to avoid being exposed to AI even if they wanted to, raising questions about how people can meaningfully consent to the use of AI in today’s society,” the researchers said in their report.

Pressure on People

As pressure grows on people to show they are not only interested in but also proficient in AI to get or retain jobs, the survey team explained that people who are opting out do not lack the skills needed to lean on chatbots.

Amid AI-fueled stock market booms, the notion that enthusiasm for AI could be on the wane would likely be seen as far-fetched in big tech boardrooms.

“The companies selling us new technology often assume that people most familiar with it will like it most,” said Jack Stilgoe of University College London.

“Our findings show that this isn’t true,” he added, warning that “people are becoming more concerned about AI over time, and even the people who use it most are ambivalent.”

Kate Devlin of King’s College London (KCL) said people need meaningful ways to consent to the use of AI, namely the ability to choose when it is applied, how it interacts with them, and how they can opt out where it matters.”



Google to Asharq Al-Awsat: AI Moves Beyond Agents Toward an Integrated Innovation Ecosystem

Anthony Nakache, Managing Director of Google for the Middle East and North Africa (Google)
Anthony Nakache, Managing Director of Google for the Middle East and North Africa (Google)
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Google to Asharq Al-Awsat: AI Moves Beyond Agents Toward an Integrated Innovation Ecosystem

Anthony Nakache, Managing Director of Google for the Middle East and North Africa (Google)
Anthony Nakache, Managing Director of Google for the Middle East and North Africa (Google)

The Middle East and North Africa ranks among the world's leading regions in AI adoption, according to Google. The company notes that the Gemini app has surpassed one billion monthly users globally, with Arabic ranking among the platform's four most widely used languages.

Within businesses, however, the picture is more complex. Most organizations are now experimenting with artificial intelligence or running pilot projects, but moving from limited trials to large-scale deployment remains challenging, particularly when it comes to data and governance.

This contrast between rapid consumer adoption and the challenges of enterprise implementation presents the region with a different test as 2030 approaches.

Anthony Nakache, Managing Director of Google for the Middle East and North Africa, explained in an exclusive interview with Asharq Al-Awsat that the next phase will not be measured solely by user numbers or infrastructure spending. Instead, success will depend on the region's ability to develop homegrown technologies and export them to global markets, rather than simply adapting solutions developed elsewhere.

The Production Test

Nakache, who has spent 18 years at Google and approximately four and a half years in the region, believes the Middle East has become a major player in the global AI landscape.

He attributes this position to a combination of factors, including government ambition, national strategies and infrastructure investment, alongside skills development, policymaking, and support for scientific research and startups.

The results of these efforts are already evident in adoption rates, particularly among consumers. The region ranks among the world's leading markets for Gemini usage, accompanied by high levels of optimism about AI's potential.

However, Nakache believes the next stage will require broader commercial adoption within organizations, eventually extending to more advanced systems, including agentic AI, which can execute multiple tasks and address increasingly complex problems.

He places trust at the center of this transition, particularly as AI systems evolve from providing answers to taking actions. He also emphasizes the importance of developing solutions that reflect local contexts alongside global technologies.

Impact Beyond Technology

Nakache points to the economic impact of Google's products in Saudi Arabia and the United Arab Emirates to illustrate how the company measures the value of technology beyond its direct services.

According to a study conducted by an independent consultancy commissioned by Google, the economic impact of the company's products across the two countries was estimated at approximately $14.2 billion in 2024.

These products include YouTube, Maps, Search, advertising, cloud computing and Android, all of which incorporate AI to varying degrees.

Nakache links this economic value to the ways individuals and businesses use these tools to search for information, make decisions, acquire skills, reach customers, and improve efficiency and security.

He also highlights employment opportunities generated by the Android and cloud computing ecosystems and YouTube's creator economy.

In his view, technological leadership is not limited to developing AI models and infrastructure. It also encompasses measurable economic and social impact.

Why Do Some Companies Struggle?

At the enterprise level, Nakache does not consider insufficient infrastructure or a lack of tools to be the only obstacles to scaling AI, although he anticipates that additional capacity will be needed to meet future demand.

The more pressing challenge, he explains, is moving from pilot projects to full implementation.

He rarely encounters an organization that is not experimenting with AI in some form. Yet experimentation does not necessarily mean that the technology has become an integral part of everyday operations.

He identifies two principal obstacles.

The first concerns data. Organizations need to understand what data they possess, how accurate and up to date it is, and how AI systems rely on that information when making decisions, even as newer models become increasingly capable of handling less structured data.

The second challenge is governance, particularly determining accountability for decisions made by agentic systems.

Nakache notes that relatively few companies he works with have established a clear framework for addressing this issue, making the transition from controlled testing environments to broader customer-facing applications more complicated.

Challenges of Practical Adoption

While data and governance are major challenges for businesses, consumers face a different difficulty: learning to use AI tools effectively.

Nakache explains that many users still struggle to obtain their desired results because the prompts they provide are too limited or unclear.

This challenge becomes more pronounced with the emergence of agentic platforms capable of automating tasks, as users increasingly need to understand how to design workflows rather than simply formulate questions.

For this reason, Google is seeking to integrate AI into products that individuals and businesses already use, rather than consistently presenting it as a separate tool.

Nakache cites Performance Max, Google's AI-powered advertising solution, as an example. The platform allows advertisers to provide creative assets and business objectives while the system manages campaign delivery across Google's products.

According to Nakache, Google has observed sales increases ranging from 14% to 20% among users of the tool globally.

The Skills Gap

Nakache believes the digital skills gap is not a new problem, but AI has made it more pressing because of the technology's advanced capabilities, associated risks, and the need for skills extending beyond traditional digital literacy.

Google says it has trained more than three million people across the region in digital skills since launching its Maharat min Google program in 2018.

The company has also committed $15 million through its AI Opportunity Initiative for the Middle East and North Africa, which aims to equip half a million people with AI skills in cooperation with local partners, including government entities, universities and business incubators.

Nakache stresses, however, that success should not be assessed solely by the number of trainees or certificates awarded. It must also reflect participants' ability to apply what they have learned in practical settings.

Accordingly, the initiative targets a diverse range of participants, including students, government employees and entrepreneurs.

Despite the region's high AI adoption rates, Nakache believes the more significant gap remains in the capabilities required to build technologies and integrate them into organizations, although some countries have succeeded in attracting international talent.

Changing Search Behavior

AI's influence also extends to Search, one of Google's oldest and largest products.

Nakache says 15% of daily searches involve queries the company has never encountered before, reflecting the continued evolution of user behavior.

As AI becomes increasingly integrated into the search experience, Google's AI Overviews feature has reached approximately 2.5 billion monthly active users, while AI Mode has reached one billion users, according to company figures.

The nature of search queries is changing as well.

Questions submitted through AI Mode are now approximately three times longer on average than conventional search queries, while more than one in six queries go beyond text to include images or other forms of interaction.

Combating Digital Fraud

Nakache acknowledges that AI has transformed the digital threat landscape, although online fraud existed long before the technology emerged.

He emphasizes, however, that Google also uses AI as one of its principal defenses against malicious activity.

According to figures he provided, the company's technologies helped block or remove approximately eight billion harmful advertisements over the past year, along with nearly 25 million accounts associated with malicious actors.

To address synthetic content, Google developed SynthID, a technology recognized by TIME magazine as one of the Best Inventions of 2026.

SynthID embeds imperceptible digital watermarks into AI-generated text, images, videos and audio without compromising their quality.

According to Google, the technology has been used to watermark more than 180 billion images and videos, as well as the equivalent of 240,000 years of audio content.

The company's content verification tools also handle approximately one million requests daily, while the technology's use is expanding to include companies such as OpenAI, NVIDIA, Kakao and Apple.

These tools help verify the presence of digital watermarks in content supported by the technology, but they do not guarantee the detection of all AI-generated material.

Nakache emphasizes that combating fraud and synthetic content cannot be the responsibility of a single company. Instead, it requires cooperation among governments, regulators, academic institutions and the private sector.

The 2030 Test

As 2030 approaches, Nakache believes the region's success in AI will be measured not only by adoption rates and investment levels, but also by its ability to develop proprietary technologies and bring them to global markets.

He considers attracting talent one of the most important factors in the transition from technology consumption to production.

Saudi Arabia, the UAE and Qatar are already developing Arabic-language models, he notes, but these efforts represent only the beginning of what the region could achieve.

The presence of Arabic speakers beyond the region's borders also provides a wider potential market for locally developed solutions.

Meanwhile, the combination of infrastructure, supportive policies, investment and skills development could enable the creation of technologies with global reach.

For Nakache, the real test by 2030 is whether the Middle East and North Africa can move beyond using technologies developed elsewhere or adapting them to local needs, and instead produce innovations that originate in its own markets and reach users around the world.

 


Democratic Victories Cloud Outlook for AI Data Center Rollout

A view of a field with a sigh against the construction of a data center, during the US midterm elections on Election Day, in Leavenworth County, Kansas, US, November 3, 2026. (Reuters)
A view of a field with a sigh against the construction of a data center, during the US midterm elections on Election Day, in Leavenworth County, Kansas, US, November 3, 2026. (Reuters)
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Democratic Victories Cloud Outlook for AI Data Center Rollout

A view of a field with a sigh against the construction of a data center, during the US midterm elections on Election Day, in Leavenworth County, Kansas, US, November 3, 2026. (Reuters)
A view of a field with a sigh against the construction of a data center, during the US midterm elections on Election Day, in Leavenworth County, Kansas, US, November 3, 2026. (Reuters)

Strong wins for Democratic candidates threaten the prospects for energy-guzzling data centers in key US states, potentially slowing the AI rollout that has carried Wall Street forward over the past four years.

The prospect of stricter regulation was weighing on stocks in AI heavyweights such as Elon Musk's SpaceX ahead of the US markets open, after drops for key chipmakers in Asia including Samsung in South Korea.

After a campaign marked by growing concerns about the environmental impacts of data centers popping up across the United States, President Donald Trump -- an enthusiastic backer of hands-off regulation for what he calls "super intelligence" -- endured a stinging rebuke of his Republican party.

Democrats gained key strongholds such as Texas, where both the Senate and governorship were won by candidates backing greater data center regulation.

"We need an immediate moratorium on data centers to last until the legislature can meet to put in place real protections so Texans can have a seat at the table to decide if and how data centers come into their communities," Gina Hinojosa, a lawyer who defeated outgoing Texas governor Greg Abbott, said during the campaign.

Abbott had wanted to make the Lone Star state the "nerve center" of artificial intelligence and data center development, but he has since noticeably shifted his stance amid a growing public backlash over energy and water provision.

Data centers notably require substantial amounts of fresh water to help cool servers, raising fears of localized shortages.

Hinojosa has urged an end to tax exemptions granted to the sector, as does fellow Democrat James Talarico, who was elected on Tuesday as a Texas senator.

Analysts had described the outcome in deeply conservative Texas as a crucial test for the future of AI infrastructure.

Thanks to its abundant energy supply and favorable regulatory framework, Texas is expected to account for nearly 30 percent of national demand for electricity dedicated to AI operations by 2028 -- a figure projected to rise sharply, according to calculations by Bloom Energy.

- Safer in space? -

Alphabet, the parent of Google, has announced plans to build several data centers in Texas, and Musk -- who spent hundreds of millions of dollars supporting the Republican camp -- has moved the headquarters of his flagship companies, Tesla, SpaceX and X, to the state.

"Data centers in space looking pretty appealing right now," Musk quipped after the vote, referring to his goal of a satellite computing network.

But investors are increasingly concerned that tougher regulations will make it harder for AI firms to make money off their massive investments.

"Democratic opposition to rapid data-center expansion could focus on power use, environmental constraints, local infrastructure strain, competition policy and the social consequences of AI deployment," said Patrick Munnelly, market strategist at the brokerage Tickmill Group.

"None of this necessarily breaks the long-term AI theme, but it can raise the hurdle rate for investment," he said.

The regulatory impact will be greatest at state level, highlighting the role of governors in responding to voter concerns.

"Given the size of the Democrats' victory, adding Texas governorship, and a 29 to 1 lead to restrict data centers, politicians that want to remain employed as politicians are going to heed these messages" about data center concerns, veteran financial analyst Jim Bianco posted on X.

In Georgia, another state with a heavy slate of data center projects, the new Democratic governor Keisha Lance Bottoms "has advocated a temporary statewide pause on new data centers, alongside requirements intended to ensure that large customers bear the costs associated with their infrastructure," noted Stephen Innes at SPI Asset Management.

Amy Acton, elected Democratic governor of Ohio, is also committing to a tougher regulatory framework on the data center buildout.


Australia’s Canva to Restructure, Affecting 22% of Workforce

A general view of the Canva headquarters after the Australian graphic design platform said it would slash 1,271 jobs in Melbourne, Australia, November 4, 2026. (Joel Carrett/AAP/via Reuters)
A general view of the Canva headquarters after the Australian graphic design platform said it would slash 1,271 jobs in Melbourne, Australia, November 4, 2026. (Joel Carrett/AAP/via Reuters)
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Australia’s Canva to Restructure, Affecting 22% of Workforce

A general view of the Canva headquarters after the Australian graphic design platform said it would slash 1,271 jobs in Melbourne, Australia, November 4, 2026. (Joel Carrett/AAP/via Reuters)
A general view of the Canva headquarters after the Australian graphic design platform said it would slash 1,271 jobs in Melbourne, Australia, November 4, 2026. (Joel Carrett/AAP/via Reuters)

Australian graphic design platform Canva Group said on Wednesday that a restructuring would affect 1,271 jobs, or around 22% of its workforce, after growth slowed for the first time in a decade.

The Sydney-based company is the latest technology firm to reduce headcount as the sector adapts to rapid advances in AI and changing business needs.

Co-founder ‌and CEO Melanie Perkins said ‌the ⁠changes would reshape Canva's ⁠organizational structure, team locations and staffing requirements.

Canva is combining its product, growth and platform teams into a single product organization aimed at reducing handovers and giving teams greater ownership.

It is also simplifying management ⁠layers and consolidating roles to improve accountability ‌and decision-making.

Canva ‌plans to make Sydney the main base ‌for more of its product teams and will ‌ask some employees to relocate. From January, most hybrid workers will be expected to attend the office two to three days a week.

The ‌graphic design firm will also provide $10,000 grants to departing employees for future ⁠endeavors

Enterprise software company Atlassian cut 1,600 jobs in March to fund further investment in AI and enterprise sales.

In February, software company WiseTech Global said it would cut nearly a third of its global workforce as part of a two-year restructuring that could rank among Australia's largest AI-linked job cuts. It later trimmed that number to about 26% in August.