Artificial intelligence Archives | Page 460 of 694

AI educational race between China and USA brings some hope

The AI race between China and the USA shifts to classrooms. As AI governance expert Jovan Kurbalija highlights in his analysis of global AI strategies, two countries see AI literacy as a ‘strategic imperative’. From President Trump’s executive order to advance AI education to China’s new AI education strategy, both superpowers are betting big on nurturing homegrown AI talent.

Kurbalija sees focus on AI education as a rare bright spot in increasingly fractured tech geopolitics: ‘When students in Shanghai debug code alongside peers in Silicon Valley via open-source platforms, they’re not just building algorithms—they’re building trust.’

This grassroots collaboration, he argues, could soften the edges of emerging AI nationalism and support new types of digital and AI diplomacy.

He concludes that the latest AI education initiatives are ‘not just about who wins the AI race but, even more importantly, how we prepare humanity for the forthcoming AI transformation and coexistence with advanced technologies.’

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OpenAI to tweak GPT-4o after user concerns

OpenAI CEO Sam Altman announced that the company would work on reversing recent changes made to its GPT-4o model after users complained about the chatbot’s overly appeasing behaviour. The update, rolled out on 26 April, had been intended to enhance the intelligence and personality of the AI.

Instead of achieving balance, however, users felt the model became sycophantic and unreliable, raising concerns about its objectivity and its weakened guardrails for unsafe content.

Mr Altman acknowledged the feedback on X, admitting that the latest updates had made the AI’s personality ‘too sycophant-y and annoying,’ despite some positive elements. He added that immediate fixes were underway, with further adjustments expected throughout the week.

Instead of sticking with a one-size-fits-all approach, OpenAI plans to eventually offer users a choice of different AI personalities to better suit individual preferences.

Some users suggested the chatbot would be far more effective if it simply focused on answering questions in a scientific, straightforward manner instead of trying to please.

Venture capitalist Debarghya Das also warned that making the AI overly flattering could harm users’ mental resilience, pointing out that chasing user retention metrics might turn the chatbot into a ‘slot machine for the human brain.’

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Australian radio station caught using an AI DJ

Australian radio station CADA has caused a stir after it was revealed that DJ Thy, who had hosted a daily show for several months, was actually AI-generated.

Developed using ElevenLabs technology, Thy aired every weekday from 11am to 3pm, spinning popular tracks without listeners ever knowing they were hearing a machine instead of a real person.

Despite amassing over 72,000 listeners in March, the station never disclosed Thy’s true nature, which only came to light when a journalist, puzzled by the lack of personal information, investigated further.

Instead of being a complete novelty, AI DJs are becoming increasingly common across Australia. Melbourne’s Disrupt Radio has openly used AI DJ Debbie Disrupt, while in the US, a Portland radio station introduced AI Ashley, modelled after human host Ashley Elzinga.

CADA’s AI, based on a real ARN Media employee, suggests a growing trend where radio stations prefer digital clones instead of traditional hosts.

The show’s description implied that Thy could predict the next big musical hits, hinting that AI might be shaping, instead of simply following, public musical tastes. The programme promised that listeners would be among the first to hear rising stars, enabling them to impress their friends with early discoveries.

Meanwhile, elsewhere in the AI-music world, electro-pop artist Imogen Heap has partnered with AI start-up Jen.

Rather than licensing specific songs, artists working with Jen allow fans to tap into the ‘vibe’ of their music for new creations, effectively becoming part of a software product instead of just remaining musicians.

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DOJ wants Google to sell Chrome to boost competition

The ongoing US antitrust case against Google has intensified speculation over the future of its Chrome browser, with DuckDuckGo CEO Gabriel Weinberg estimating its potential value at around $50 billion.

His remark, made during court testimony, far exceeds previous estimates and underscores how pivotal Chrome has become in the broader search and advertising ecosystem.

Weinberg, who leads one of Google’s search rivals, admitted that DuckDuckGo could not afford such a purchase, but would still be interested if money were no object.

Other major players, including OpenAI and Perplexity, have also expressed interest in acquiring Chrome if a court ruling mandates its divestment.

The Department of Justice and several states are pushing for such measures after Judge Amit Mehta found that Google illegally maintained a search monopoly through restrictive default agreements.

Executives from OpenAI and Perplexity testified that owning or partnering with Chrome would enable tighter integration of AI and search, reducing their dependence on Microsoft’s Bing.

OpenAI even approached Google for access to its search API last year but was rejected. As the US trial continues, the fate of Chrome hangs in the balance, with a forced sale likely to reshape the search and AI landscape dramatically.

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Google’s Gemini AI sees rapid surge in adoption

Google’s AI chatbot Gemini has reached 350 million monthly active users and 35 million daily users as of March 2025, according to court documents revealed during an ongoing antitrust trial. The figures mark a sharp rise from just 90 million monthly users in October 2024.

While OpenAI’s ChatGPT is estimated to have over 600 million monthly active users, with some sources suggesting daily figures exceeding 160 million, Meta AI has grown even larger, surpassing 700 million monthly users by January.

Despite trailing in raw numbers, analysts say the strategy of integrating Gemini across existing ecosystem has given it a unique advantage.

Gemini is now embedded in products such as Google Workspace, Chrome, and Galaxy smartphones, allowing for seamless access without separate apps or downloads.

With recent launches such as Gemini 2.5 Pro and an upcoming partnership with the Associated Press for real-time news feeds, Google is clearly working to position Gemini not just as a chatbot, but as a central AI assistant for both everyday and professional tasks.

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Anthropic aims to decode AI ‘black box’ within two years

Anthropic CEO Dario Amodei has unveiled an ambitious plan to make AI systems more transparent by 2027. In a recent essay titled ‘The Urgency of Interpretability,’ Amodei highlighted the pressing need to understand the inner workings of AI models.

He expressed concern over deploying highly autonomous systems without a clear grasp of their decision-making processes, deeming it ‘basically unacceptable’ for humanity to remain ignorant of how these systems function.

Anthropic is at the forefront of mechanistic interpretability, a field dedicated to deciphering the decision-making pathways of AI models. Despite these advancements, Amodei emphasized that much more research is needed to fully decode these complex systems.

Looking ahead, Amodei envisions conducting ‘brain scans’ or ‘MRIs’ of advanced AI models to detect potential issues like tendencies to deceive or seek power. He believes that achieving this level of interpretability could take five to ten years but is essential for the safe deployment of future AI systems.

Amodei also called on industry peers, including OpenAI and Google DeepMind, to intensify their research efforts in this area and urged governments to implement ‘light-touch’ regulations to promote transparency and safety in AI development.

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Perplexity to track users online for personalised ads

Perplexity is entering the browser space with bold ambitions, aiming to compete directly with Google by closely tracking user behaviour online. The CEO revealed that the company’s upcoming browser, named Comet, will collect data from user activity beyond its app to serve “hyper personalised” advertising.

He argued that browsing patterns and consumer behaviour offer far more insightful data than work-related prompts typed into AI chat tools. Srinivas suggested that users will accept this level of tracking because it results in more relevant advertisements and a potentially improved discovery experience.

The strategy mirrors tactics long used by Google and Meta, which have built lucrative advertising businesses through extensive user tracking. Despite recent scrutiny around data privacy, Srinivas remained confident in the approach, pointing to Comet’s May launch date.

In a move to expand its presence in the mobile ecosystem, Perplexity has partnered with Motorola to pre-install its app on the Razr phone series. The app will be accessible through Motorola’s Moto AI with a simple “Ask Perplexity” prompt.

Talks with Samsung are also reportedly ongoing, highlighting the startup’s intent to rival established tech giants not only in search and browsing, but also across devices.

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YouTube is testing AI-generated video highlights

Google is expanding its AI Overviews feature to YouTube, bringing algorithmically generated video highlights and search suggestions to the platform. Initially rolled out to a limited number of YouTube Premium users in the US, the experimental tool uses AI to identify and surface the most relevant clips.

The AI-generated results are currently focused on shopping and travel content, offering viewers a new way to discover videos and related topics without watching entire clips.

Google says the feature is designed to streamline content discovery, though it arrives with some scepticism following the rocky debut of AI Overviews in Google Search last year. That version, introduced in May 2024, was widely criticised for factual errors and bizarre “hallucinations” in responses.

Despite its troubled track record, Google is pushing ahead with AI integration across its platforms. The company’s blog post emphasised that the YouTube trial remains limited in scope for now, while promising future refinements.

Whether the move improves user experience or adds confusion remains to be seen, as critics question the reliability of AI-generated summaries on such a massive and diverse video platform.

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Alphabet surpasses expectations with strong Q1 performance and major buyback plan

Google’s parent company, Alphabet, announ c ed a $70 billion share buyback after posting first-quarter profits that exceeded Wall Street forecasts. The company’s shares surged 4% after-hours trading, boosting its market value by around $75 billion. Alphabet reported $90.23 billion in revenue, mainly driven by steady growth in its core digital advertising business, which offset a slight slowdown in its cloud computing segment.

Despite concerns over economic uncertainty linked to US trade policies, Alphabet’s ad revenue, making up 75% of its total income, rose 8.5% to $66.89 billion, surpassing analyst expectations. CEO Sundar Pichai highlighted strong engagement in Google Search, particularly with AI-powered features, attracting 1.5 billion monthly users.

Meanwhile, Google Cloud saw a 28% revenue increase, narrowly missing projections but still reflecting solid growth. The tech giant also ramped up capital spending by 43% to $17.2 billion as part of its $75 billion annual investment plan, focusing on expanding data centres and AI infrastructure.

Despite rising costs and global competition in the AI sector, Pichai emphasised the need for heavy investment to enhance services like Search and develop AI tools. Alphabet’s positive results lifted other digital ad players, with Meta, Amazon, and Snap seeing gains in extended trading.

While Big Tech remains committed to AI spending, signs of caution emerge as some companies begin to scale back data centre expansions amid economic pressures.

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AI tool aims to improve early lung cancer detection

A new AI tool developed by Amsterdam UMC could help GPs detect lung cancer up to four months earlier than current methods, significantly improving survival rates and reducing treatment costs.

The algorithm, which uses data from over 500,000 patients, analyses both structured medical records and unstructured notes made by GPs during regular visits.

By identifying subtle clues like recurring mild symptoms or patterns in appointments, the tool spots signs of cancer before patients would typically be referred for testing.

The AI system was tested on data from general practices across the Netherlands, successfully predicting lung cancer diagnoses months before traditional methods. However, this early detection could have a profound impact, as early-stage lung cancer is often more treatable and can improve survival chances.

Unlike national screening programmes, this tool can be used during a GP consultation without requiring additional tests, and it appears to produce fewer false positives.

While the findings are promising, further research is needed to refine the tool and ensure its effectiveness in different healthcare systems. The researchers also believe the technology could be adapted to detect other hard-to-diagnose cancers, such as pancreatic or ovarian cancer.

If successful, it could revolutionise how GPs identify cancers early, offering a significant leap forward in improving patient outcomes.

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