Development Archives | Page 346 of 548 | Digital Watch Observatory

Russian governor proposes gas-powered Bitcoin mining solution

A Russian provincial governor has proposed a solution to Bitcoin mining-related energy shortages. He suggested that associated gas from oil drilling sites could power mining operations.

Irkutsk Governor Igor Kobzev suggested that crypto miners collaborate with oil and gas companies to build data centres powered by alternative fuels. The suggestion comes amidst mounting energy concerns, especially after the recent year-round ban on Bitcoin mining in southern Irkutsk.

Governor Kobzev stated that the regional government supports Bitcoin mining but is committed to ensuring reliable electricity for residents and businesses.

He pointed out that mining operations should address the region’s electricity shortages. The government is ready to facilitate partnerships between miners and the oil and gas sectors.

Russian companies like BitRiver and Gazprom Neft have already experimented with using associated gas to power crypto mining facilities.

The Ministry of Energy is reportedly considering additional regional mining bans due to the strain on electricity networks.

Despite concerns, Governor Kobzev supports associated gas-powered mining, viewing it as a solution to reduce flaring and the environmental impact.

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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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AI tool improves accuracy in detecting heart disease

A team of researchers at Mount Sinai Hospital in New York has successfully calibrated an AI tool to more accurately assess the likelihood of hypertrophic cardiomyopathy (HCM) in patients.

By assigning specific probability scores, the AI model now offers clearer guidance to clinicians and patients regarding disease risk.

HCM, a thickening of the heart muscle that affects around one in 200 people globally, can lead to serious complications such as heart failure or sudden cardiac death.

The Viz HCM algorithm, already approved by the US Food and Drug Administration, previously provided vague classifications like ‘suspected HCM.’ Thanks to model calibration, clinicians can now give patients more precise estimates—for instance, a 60% probability of having the condition.

Researchers ran the algorithm on nearly 71,000 patients who had undergone electrocardiograms between March 2023 and January 2024. Out of these, 1,522 were flagged by the AI, with further review of medical records and imaging confirming diagnoses.

The results validated that the newly calibrated probabilities closely reflected real-world outcomes, improving the tool’s accuracy and practical utility.

Experts say this advancement enhances clinical workflows by helping doctors prioritise patients based on their actual risk levels.

Beyond technological innovation, the study marks a step forward in integrating AI responsibly into everyday clinical practice—making healthcare more personalised, interpretable, and effective.

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Auto Shanghai 2025 showcases cutting-edge AI robots

At Auto Shanghai 2025, running from April 23 to May 2, nearly 1,000 companies from 26 countries showcase their innovations.

A major highlight of the event has been the introduction of AI humanoid robots.

Among the most talked-about innovations is Mornine Gen-1, an AI humanoid robot developed by Chinese automaker Chery.

Designed to resemble a young woman, Mornine is set for various roles, from auto sales consultation to retail guidance and entertainment performances.

Also drawing attention is AgiBot’s A2 interactive service robot. Serving as a ‘sales consultant,’ the A2’s smart, interactive features have made it a standout at the event.

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Microsoft’s Surface ad uses generative AI without anyone noticing

Microsoft recently revealed that it created a minute-long ad for its Surface Pro and Surface Laptop using generative AI, but the twist is that no one seemed to notice the AI elements, even though the ad has been online for nearly three months.

Released on January 30th, the ad features a mix of real footage and AI-generated content, with some AI-generated visuals corrected and integrated with live shots.

The AI tools were first used to generate the script, storyboards, and pitch deck for the ad. From there, a combination of text prompts and sample images helped generate visuals, which were iterated on and refined with image and video generators like Hailuo and Kling.

Creative director Cisco McCarthy explained that it took thousands of prompts to achieve the desired results, although the process ultimately saved the team around 90% of the time and cost typically needed for such a production.

Despite the AI involvement, most viewers didn’t notice the difference. The ad has received over 40,000 views on YouTube, but none of the top comments suggest AI was used. The quick-cut editing style helped mask the AI output’s flaws, demonstrating how powerful generative AI has become in the right hands.

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North Korean hackers create fake US firms to target crypto developers

North Korea’s Lazarus Group has launched a sophisticated campaign to infiltrate the cryptocurrency industry by registering fake companies in the US and using them to lure developers into downloading malware.

According to a Reuters investigation, these US-registered shell companies, including Blocknovas LLC and Softglide LLC, were set up using false identities and addresses, giving the operation a veneer of legitimacy instead of drawing suspicion.

Once established, the fake firms posted job listings through legitimate platforms like LinkedIn and Upwork to attract developers. Applicants were guided through fake interview processes and instructed to download so-called test assignments.

Instead of harmless software, the files installed malware that enabled the hackers to steal passwords, crypto wallet keys, and other sensitive information.

The FBI has since seized Blocknovas’ domain and confirmed its connection to Lazarus, labelling the campaign a significant evolution in North Korea’s cyber operations.

These attacks were supported by Russian infrastructure, allowing Lazarus operatives to bypass North Korea’s limited internet access.

Tools such as VPNs and remote desktop software enabled them to manage operations, communicate over platforms like GitHub and Telegram, and even record training videos on how to exfiltrate data.

Silent Push researchers confirmed that the campaign has impacted hundreds of developers and likely fed some stolen access to state-aligned espionage units instead of limiting the effort to theft.

Officials from the US, South Korea, and the UN say the revenue from such cyberattacks is funneled into North Korea’s nuclear missile programme. The FBI continues to investigate and has warned that not only the hackers but also those assisting their operations could face serious consequences.

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Google boosts AI in coding and cloud growth

More than 30% of all code at Google is now written with the help of AI, according to CEO Sundar Pichai during Alphabet’s Q1 2025 earnings call.

Developers are embracing AI-generated suggestions in nearly one out of every three code changes, thanks to improved models and the rollout of agentic workflows—AI systems designed to manage complex, multi-step tasks.

Pichai noted that AI-assisted coding is expanding across the company, with customer service teams leading the way in adoption.

Alphabet reported strong financial results, with quarterly revenue climbing 12% year-over-year to $90.2 billion. Net income rose sharply by 46% to $34.5 billion, and earnings per share jumped 49%.

While there was a slight quarterly dip in revenue from the previous quarter, Google’s core advertising business, YouTube, and Google Cloud all contributed to year-on-year growth. Cloud revenue, in particular, increased 28% due to surging demand for AI and infrastructure products.

The recently released Gemini 2.5 Pro model was described by Pichai as ‘state-of-the-art’, outperforming rivals across benchmarks and landing the top spot on Chatbot Arena. Gemini models are now integrated across 15 Google products used by more than half a billion people.

Features like Gemini Live and AI-powered camera tools are being rolled out on Android and Pixel devices, while Google Assistant will also receive a Gemini upgrade later this year.

Instead of slowing down, Google is accelerating its AI development with initiatives like Gemini Robotics Models, the AI Co-Scientist for research, and the continued success of AlphaFold, used by over 2.5 million scientists.

With over 200% growth in users of AI Studio and Gemini API, and more than 140 million downloads of Gemma models, Google is clearly positioning AI at the centre of its future across products, platforms, and research.

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ChatGPT expands Deep Research to more users

A new feature introduced by ChatGPT in February, called Deep Research, is gradually becoming available across its user base. This includes subscribers on the Plus, Team, and Pro plans, while even those using the free ChatGPT app on iOS and Android can now access a simplified version.

Designed to carry out in-depth reports and analyses within minutes, Deep Research uses OpenAI’s o3 model to perform tasks that would otherwise take people hours to complete.

Instead of limiting access to paid users alone, OpenAI has rolled out a lightweight version powered by its o4-mini AI model for free users. Although responses are shorter, the company insists the quality and depth remain comparable.

The more efficient model also helps reduce costs, while delivering what OpenAI calls ‘nearly as intelligent’ results as the full version.

The feature’s capabilities stretch from suggesting personalised product purchases like cars or TVs, to helping with complex decisions such as choosing a university or analysing market trends.

Free-tier users are currently allowed up to five Deep Research tasks each month, whereas Plus and Team plans get ten full and fifteen lightweight tasks. Pro users enjoy a generous 125 tasks of each version per month, and EDU and Enterprise plans will begin access next week.

Once users hit their full version limit, they’ll be automatically shifted to the lightweight tool instead of losing access altogether. Meanwhile, Google’s GeminiAI offers a similar function for its paying customers, also aiming to deliver quick, human-level research and analysis.

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TSMC targets AI future with advanced chip designs

Taiwan Semiconductor Manufacturing Co. (TSMC) has introduced its cutting-e d ge A14 logic process technology at its North America Technology Symposium, held in Santa Clara, California.

The A14 process, touted as a major leap from its N2 predecessor, is aimed at enhancing AI capabilities through faster computing speeds and greater power efficiency. TSMC expects the A14 to enter production in 2028 and reports that development is ahead of schedule in terms of yield performance.

Alongside the A14, TSMC revealed significant advances in its Chip on Wafer on Substrate (CoWoS) technology, crucial for meeting AI’s growing demands for processing power and high-bandwidth memory.

A new SoW-X platform, based on CoWoS and capable of 40 times more computing power than current solutions, is slated for mass production in 2027. The company also confirmed plans to scale up its 9.5 reticle size CoWoS for volume production in the same year.

TSMC continues to broaden its innovation pipeline with developments across various domains, including 3D chip stacking and advanced packaging. It also unveiled the N4C RF, its latest radio frequency technology designed to support upcoming standards like WiFi8 and AI-powered audio platforms.

Risk production of the N4C RF is expected in early 2026, as TSMC strengthens its foothold in high-performance computing, mobile, automotive, and IoT markets.

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