Artificial intelligence Archives | Page 395 of 689

ChatGPT quietly tests new ‘Study Together’ feature for education

A few ChatGPT users have noticed a new option called ‘Study Together’ appearing among available tools, though OpenAI has yet to confirm any official rollout. The feature seems designed to make ChatGPT a more interactive educational companion than just delivering instant answers.

Rather than offering direct solutions, the tool prompts users to think for themselves by asking questions, potentially turning ChatGPT into a digital tutor.

Some speculate the mode might eventually allow multiple users to study together in real-time, mimicking a virtual study group environment.

With the chatbot already playing a significant role in classrooms — helping teachers plan lessons or assisting students with homework — the ‘Study Together’ feature might help guide users toward deeper learning instead of enabling shortcuts.

Critics have warned that AI tools like ChatGPT risk undermining education, so it could be a strategic shift to encourage more constructive academic use.

OpenAI has not confirmed when or if the feature will launch publicly, or whether it will be limited to ChatGPT Plus users. When asked, ChatGPT only replied that nothing had been officially announced.

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Sam Altman shrugs off Meta poaching, backs Trump, jabs at Musk

OpenAI CEO Sam Altman addressed multiple hot topics during the Sun Valley conference, including Meta’s aggressive recruitment of top AI researchers, his strained relationship with Elon Musk, and a surprising show of support for Donald Trump.

Altman downplayed Meta’s talent raids, saying he had not spoken to Mark Zuckerberg since the Meta CEO lured away three OpenAI researchers with a $100 million signing bonus. All three had worked at OpenAI’s Zurich office, which opened in 2024.

Despite the losses, Altman described the situation as ‘fine’ and ‘good’, suggesting OpenAI’s mission continues to retain top talent.

The OpenAI chief also took a subtle swipe at Meta’s smartglasses, saying he doesn’t like wearable tech and implying his company has no plans to follow suit.

On the topic of Elon Musk, Altman laughed off their rivalry, saying only that Musk’s bust-ups with everybody, and hinting at the long-running tension between the two former co-founders.

Perhaps most notably, Altman expressed disillusionment with the Democratic Party, saying he no longer feels represented by mainstream figures he once supported.

He praised Donald Trump’s focus on AI infrastructure. He even donated $1 million to Trump’s inaugural fund — a gesture reflecting a broader shift among Silicon Valley leaders warming to Trump as his popularity rises.

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AI-made music sparks emotional authenticity debate

Innovative AI group The Velvet Sundown has produced retro‑style blues‑rock and indie pop tracks entirely without human musicians.

While the music echoes 1970s and 80s sounds, discussions have emerged over whether these digital creations truly capture emotional depth.

Many listeners find the melodies catchy and stylistically accurate, yet some critics argue AI‑generated music lacks the spontaneity, lived experience and nuance that human artists bring.

Skeptics contend that an AI’s technical precision cannot replicate the intangible aspects of musical performance.

The rise of AI in music has opened creative possibilities but also triggered deeper cultural questions. Can technology ever replace genuine emotion, or will it remain a stylistic tool?

Experts agree human creativity remains vital, AI can enhance, but not fully substitute, the soul‑stirring impulse of authentic music-making.

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AI model detects infections from wound photos

Mayo Clinic researchers have developed an AI system capable of detecting surgical site infections from wound photographs submitted by patients. The model was trained using over 20,000 images from more than 6,000 persons across nine hospital locations.

The AI pipeline identifies whether a photo contains a surgical incision and then evaluates that incision for infection. Known as Vision Transformer, the model accurately recognises incisions and scores high in AUC in infection detection.

Medical staff review outpatient wound images manually, which can delay care and burden resources. Automating this process may improve early diagnosis, reduce unnecessary visits, and speed up responses to high-risk cases.

Researchers believe the tool could eventually serve as a frontline screening method, especially helpful in rural or understaffed areas. Consistent performance across diverse patient groups also suggests a lower risk of algorithmic bias, though further validation remains essential.

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OpenAI locks down operations after DeepSeek model concerns

OpenAI has significantly tightened its internal security following reports that DeepSeek may have replicated its models. DeepSeek allegedly used distillation techniques to launch a competing product earlier this year, prompting a swift response.

OpenAI has introduced strict access protocols to prevent information leaks, including fingerprint scans, offline servers, and a policy restricting internet use without approval. Sensitive projects such as its AI o1 model are now discussed only by approved staff within designated areas.

The company has also boosted cybersecurity staffing and reinforced its data centre defences. Confidential development information is now shielded through ‘information tenting’.

These actions coincide with OpenAI’s $30 billion deal with Oracle to lease 4.5 gigawatts of data centre capacity across the United States. The partnership plays a central role in OpenAI’s growing Stargate infrastructure strategy.

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Phishing 2.0: How AI is making cyber scams more convincing

Phishing remains among the most widespread and dangerous cyber threats, especially for individuals and small businesses. These attacks rely on deception—emails, texts, or social messages that impersonate trusted sources to trick people into giving up sensitive information.

Cybercriminals exploit urgency and fear. A typical example is a fake email from a bank saying your account is at risk, prompting you to click a malicious link. Even when emails look legitimate, subtle details—like a strange sender address—can be red flags.

In one recent scam, Netflix users received fake alerts about payment failures. The link led to a fake login page where credentials and payment data were stolen. Similar tactics have been used against QuickBooks users, small businesses, and Microsoft 365 customers.

Small businesses are frequent targets due to limited security resources. Emails mimicking vendors or tech companies often trick employees into handing over credentials, giving attackers access to sensitive systems.

Phishing works because it preys on human psychology: trust, fear, and urgency. And with AI, attackers can now generate more convincing content, making detection harder than ever.

Protection starts with vigilance. Always check sender addresses, avoid clicking suspicious links, and enable multi-factor authentication (MFA). Employee training, secure protocols for sensitive requests, and phishing simulations are critical for businesses.

Phishing attacks will continue to grow in sophistication, but with awareness and layered security practices, users and businesses can stay ahead of the threat.

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Groq opens AI data centre in Helsinki

Groq has opened its first European AI data centre in Helsinki, Finland, in collaboration with Equinix. The facility offers European users fast, secure, and low-latency AI inference services, aiming to improve performance and data governance.

The launch follows Groq’s existing partnership with Equinix, which already includes a site in Dallas. The new centre complements Groq’s global network, including facilities in the US, Canada and Saudi Arabia.

CEO Jonathan Ross stated the centre provides immediate infrastructure for developers building fast at scale. Equinix highlighted Finland’s reliable power and sustainable energy as key factors in the decision to host capacity there.

The data centre supports GroqCloud, delivering over 20 million tokens per second across its network. European businesses are expected to benefit from improved AI performance and operational efficiency.

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Training AI sustainably depends on where and how

Organisations are urged to place AI model training in regions powered by renewable energy. For instance, training in Canada rather than Poland could reduce carbon emissions by approximately 85 %. Strategic location choices are becoming vital for greener AI.

Selecting appropriate hardware also plays a pivotal role. Research shows that a high-end NVIDIA H100 GPU carries three times the manufacturing carbon footprint of a more energy-efficient NVIDIA L4. Opting for the proper GPU can deliver performance without undue environmental cost.

Efficiency should be embedded at every stage of the AI process. From hardware procurement and algorithm design to operational deployment, even fractional improvements across the supply chain can significantly reduce overall carbon output, ensuring that today’s progress doesn’t harm tomorrow’s planet.

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US Cyber Command proposes $5M AI Initiative for 2026 budget

US Cyber Command is seeking $5 million in its fiscal year 2026 budget to launch a new AI project to advance data integration and operational capabilities.

While the amount represents a small fraction of the command’s $1.3 billion research and development (R&D) portfolio, the effort reflects growing emphasis on incorporating AI into cyber operations.

The initiative follows congressional direction set in the fiscal year (FY) 2023 National Defense Authorization Act, which tasked Cyber Command and the Department of Defense’s Chief Information Officer—working with the Chief Digital and Artificial Intelligence Officer, DARPA, the NSA, and the Undersecretary of Defense for Research and Engineering—to produce a five-year guide and implementation plan for rapid AI adoption.

However, this roadmap, developed shortly after, identified priorities for deploying AI systems, applications, and supporting data processes across cyber forces.

Cyber Command formed an AI task force within its Cyber National Mission Force (CNMF) to operationalise these priorities. The newly proposed funding would support the task force’s efforts to establish core data standards, curate and tag operational data, and accelerate the integration of AI and machine learning solutions.

Known as Artificial Intelligence for Cyberspace Operations, the project will focus on piloting AI technologies using an agile 90-day cycle. This approach is designed to rapidly assess potential solutions against real-world use cases, enabling quick iteration in response to evolving cyber threats.

Budget documents indicate the CNMF plans to explore how AI can enhance threat detection, automate data analysis, and support decision-making processes. The command’s Cyber Immersion Laboratory will be essential in testing and evaluating these cyber capabilities, with external organisations conducting independent operational assessments.

The AI roadmap identifies five categories for applying AI across Cyber Command’s enterprise: vulnerabilities and exploits; network security, monitoring, and visualisation; modelling and predictive analytics; persona and identity management; and infrastructure and transport systems.

To fund this effort, Cyber Command plans to shift resources from its operations and maintenance account into its R&D budget as part of the transition from FY2025 to FY2026.

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How agentic AI is transforming cybersecurity

Cybersecurity is gaining a new teammate—one that never sleeps and acts independently. Agentic AI doesn’t wait for instructions. It detects threats, investigates, and responds in real-time. This new class of AI is beginning to change the way we approach cyber defence.

Unlike traditional AI systems, Agentic AI operates with autonomy. It sets objectives, adapts to environments, and self-corrects without waiting for human input. In cybersecurity, this means instant detection and response, beyond simple automation.

With networks more complex than ever, security teams are stretched thin. Agentic AI offers relief by executing actions like isolating compromised systems or rewriting firewall rules. This technology promises to ease alert fatigue and keep up with evasive threats.

A 2025 Deloitte report says 25% of GenAI-using firms will pilot Agentic AI this year. SailPoint found that 98% of organisations will expand AI agent use in the next 12 months. But rapid adoption also raises concern—96% of tech workers see AI agents as security risks.

The integration of AI agents is expanding to cloud, endpoints, and even physical security. Yet with new power comes new vulnerabilities—from adversaries mimicking AI behaviour to the risk of excessive automation without human checks.

Key challenges include ethical bias, unpredictable errors, and uncertain regulation. In sectors like healthcare and finance, oversight and governance must keep pace. The solution lies in balanced control and continuous human-AI collaboration.

Cybersecurity careers are shifting in response. Hybrid roles such as AI Security Analysts and Threat Intelligence Automation Architects are emerging. To stay relevant, professionals must bridge AI knowledge with security architecture.

Agentic AI is redefining cybersecurity. It boosts speed and intelligence but demands new skills and strong leadership. Adaptation is essential for those who wish to thrive in tomorrow’s AI-driven security landscape.

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