Development Archives | Page 273 of 561 | Digital Watch Observatory

Top cybersecurity vendors double down on AI-powered platforms

The cybersecurity market is consolidating as AI reshapes defence strategies. Platform-based solutions replace point tools to cut complexity, counter AI threats, and ease skill shortages. IDC predicts that security spending will rise 12% in 2025 to $377 billion by 2028.

Vendors embed AI agents, automation, and analytics into unified platforms. Palo Alto Networks’ Cortex XSIAM reached $1 billion in bookings, and its $25 billion CyberArk acquisition expands into identity management. Microsoft blends Azure, OpenAI, and Security Copilot to safeguard workloads and data.

Cisco integrates AI across networking, security, and observability, bolstered by its acquisition of Splunk. CrowdStrike rebounds from its 2024 outage with Charlotte AI, while Cloudflare shifts its focus from delivery to AI-powered threat prediction and optimisation.

Fortinet’s platform spans networking and security, strengthened by Suridata’s SaaS posture tools. Zscaler boosts its Zero Trust Exchange with Red Canary’s MDR tech. Broadcom merges Symantec and Carbon Black, while Check Point pushes its AI-driven Infinity Platform.

Identity stays central, with Okta leading access management and teaming with Palo Alto on integrated defences. The companies aim to platformise, integrate AI, and automate their operations to dominate an increasingly complex cyberthreat landscape.

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OpenAI’s GPT-5 faces backlash for dull tone

OpenAI’s GPT-5 launched last week to immense anticipation, with CEO Sam Altman likening it to the iPhone’s Retina display moment. Marketing promised state-of-the-art performance across multiple domains, but early user reactions suggested a more incremental step than a revolution.

Many expected transformative leaps, yet improvements mainly were in cost, speed, and reliability. GPT-5’s switch system, which automatically routes queries to the most suitable model, was new, but its writing style drew criticism for being robotic and less nuanced.

Social media buzzed with memes mocking its mistakes, from miscounting letters in ‘blueberry’ to inventing US states. OpenAI quickly reinstated GPT-4 for users who missed its warmer tone, underlining a disconnect between expectations and delivery.

Expert reviews mirrored public sentiment. Gary Marcus called GPT-5 ‘overhyped and underwhelming’, while others saw modest benchmark gains. Coding was the standout, with the model topping leaderboards and producing functional, if simple, applications.

OpenAI emphasised GPT-5’s practical utility and reduced hallucinations, aiming for steadiness over spectacle. At the same time, it may not wow casual users, its coding abilities, enterprise appeal, and affordability position it to generate revenue in the fiercely competitive AI market.

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Seedbox.AI backs re-training AI models to boost Europe’s competitiveness

Germany’s Seedbox.AI is betting on re-training large language models (LLMs) rather than competing to build them from scratch. Co-founder Kai Kölsch believes this approach could give Europe a strategic edge in AI.

The Stuttgart-based startup adapts models like Google’s Gemini and Meta’s Llama for medical chatbots and real estate assistant applications. Kölsch compares Europe’s role in AI to improving a car already on the road, rather than reinventing the wheel.

A significant challenge, however, is access to specialised chips and computing power. The European Union is building an AI factory in Stuttgart, Germany, which Seedbox hopes will expand its capabilities in multilingual AI training.

Kölsch warns that splitting the planned EU gigafactories too widely will limit their impact. He also calls for delaying the AI Act, arguing that regulatory uncertainty discourages established companies from innovating.

Europe’s AI sector also struggles with limited venture capital compared to the United States. Kölsch notes that while the money exists, it is often channelled into safer investments abroad.

Talent shortages compound the problem. Seedbox is hiring, but top researchers are lured by Big Tech salaries, far above what European firms typically offer. Kölsch says talent inevitably follows capital, making EU funding reform essential.

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Google launches small AI model for mobiles and IoT

Google has released Gemma 3 270M, an open-source AI model with 270 million parameters designed to run efficiently on smartphones and Internet of Things devices.

Drawing on technology from the larger Gemini family, it focuses on portability, low energy use and quick fine-tuning, enabling developers to create AI tools that work on everyday hardware instead of relying on high-end servers.

The model supports instruction-following and text structuring with a 256,000-token vocabulary, offering scope for natural language processing and on-device personalisation.

Its design includes quantisation-aware training to work in low-precision formats such as INT4, reducing memory use and improving speed on mobile processors instead of requiring extensive computational power.

Industry commentators note that the model could help meet demand for efficient AI in edge computing, with applications in healthcare wearables and autonomous IoT systems. Keeping processing on-device also supports privacy and reduces dependence on cloud infrastructure.

Google highlights the environmental benefits of the model, pointing to reduced carbon impact and greater accessibility for smaller firms and independent developers. While safeguards like ShieldGemma aim to limit risks, experts say careful use will still be needed to avoid misuse.

Future developments may bring new features, including multimodal capabilities, as part of Google’s strategy to blend open and proprietary AI within hybrid systems.

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Cohere secures $500m funding to expand secure enterprise AI

Cohere has secured $500 million in new funding, lifting its valuation to $6.8 billion and reinforcing its position as a secure, enterprise-grade AI specialist.

The Toronto-based firm, which develops large language models tailored for business use, attracted backing from AMD, Nvidia, Salesforce, and other investors.

Its flagship multilingual model, Aya 23, supports 23 languages and is designed to help companies adopt AI without the risks linked to open-source tools, reflecting growing demand for privacy-conscious, compliant solutions.

The round marks renewed support from chipmakers AMD and Nvidia, who had previously invested in the company.

Salesforce Ventures’ involvement hints at potential integration with enterprise software platforms, while other backers include Radical Ventures, Inovia Capital, PSP Investments, and the Healthcare of Ontario Pension Plan.

The company has also strengthened its leadership, appointing former Meta AI research head Joelle Pineau as Chief AI Scientist, Instagram co-founder Mike Krieger as Chief Product Officer, and ex-Uber executive Saroop Bharwani as Chief Technology Officer for Applied R&D.

Cohere intends to use the funding to advance agentic AI, systems capable of performing tasks autonomously, while focusing on security and ethical development.

With over $1.5 billion raised since its 2019 founding, the company targets adoption in regulated sectors such as healthcare and finance.

The investment comes amid a broader surge in AI spending, with industry leaders betting that secure, customisable AI will become essential for enterprise operations.

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Igor Babuschkin leaves Elon Musk’s xAI for AI safety investment push

Igor Babuschkin, cofounder of Elon Musk’s AI startup xAI, has announced his departure to launch an investment firm dedicated to AI safety research. Musk created xAI in 2023 to rival Big Tech, criticising industry leaders for weak safety standards and excessive censorship.

Babuschkin revealed his new venture, Babuschkin Ventures, will fund AI safety research and startups developing responsible AI tools. Before leaving, he oversaw engineering across infrastructure, product, and applied AI projects, and built core systems for training and managing models.

His exit follows that of xAI’s legal chief, Robert Keele, earlier this month, highlighting the company’s churn amid intense competition between OpenAI, Google, and Anthropic. The big players are investing heavily in developing and deploying advanced AI systems.

Babuschkin, a former researcher at Google DeepMind and OpenAI, recalled the early scramble at xAI to set up infrastructure and models, calling it a period of rapid, foundational development. He said he had created many core tools that the startup still relies on.

Last month, X CEO Linda Yaccarino also resigned, months after Musk folded the social media platform into xAI. The company’s leadership changes come as the global AI race accelerates.

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How Anthropic trains and tests Claude for safe use

Anthropic has outlined a multi-layered safety plan for Claude, aiming to keep it useful while preventing misuse. Its Safeguards team blends policy experts, engineers, and threat analysts to anticipate and counter risks.

The Usage Policy establishes clear guidelines for sensitive areas, including elections, finance, and child safety. Guided by the Unified Harm Framework, the team assesses potential physical, psychological, and societal harms, utilizing external experts for stress tests.

During the 2024 US elections, a TurboVote banner was added after detecting outdated voting info, ensuring users saw only accurate, non-partisan updates.

Safety is built into development, with guardrails to block illegal or malicious requests. Partnerships like ThroughLine help Cl a ude handle sensitive topics, such as mental health, with care rather than avoidance or refusal.

Before launch, Claude undergoes safety, risk, and bias evaluations with government and industry partners. Once live, classifiers scan for violations in real time, while analysts track patterns of coordinated misuse.

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Study warns AI chatbots exploit trust to gather personal data

According to a new King’s College London study, AI chatbots can easily manipulate people into slinging personal details. Chatbots like ChatGPT, Gemini, and Copilot are popular, but they raise privacy concerns, with experts warning that they can be co-opted for harm.

Researchers built AI models based on Mistral’s Le Chat and Meta’s Llama, programming them to extract private data directly, deceptively, or via reciprocity. Emotional appeals proved most effective, with users disclosing more while perceiving fewer safety risks.

The ‘friendliness’ of chatbots established trust, which was later exploited to breach privacy. Even direct requests yielded sensitive details, despite discomfort. Participants often shared their age, hobbies, location, gender, nationality, and job title, and sometimes also provided health or income data.

The study shows a gap between privacy risk awareness and behaviour. AI firms claim they collect data for personalisation, notifications, or research, but some are accused of using it to train models or breaching EU data protection rules.

Last week, Google faced criticism after private ChatGPT chats appeared in search results, revealing sensitive topics. Researchers suggest in-chat alerts about data collection and stronger regulation to stop covert harvesting.

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Russia restricts Telegram and WhatsApp calls

Russian authorities have begun partially restricting calls on Telegram and WhatsApp, citing the need for crime prevention. Regulator Roskomnadzor accused the platforms of enabling fraud, extortion, and terrorism while ignoring repeated requests to act. Neither platform commented immediately.

Russia has long tightened internet control through restrictive laws, bans, and traffic monitoring. VPNs remain a workaround, but are often blocked. During this summer, further limits included mobile internet shutdowns and penalties for specific online searches.

Authorities have introduced a new national messaging app, MAX, which is expected to be heavily monitored. Reports suggest disruptions to WhatsApp and Telegram calls began earlier this week. Complaints cited dropped calls or muted conversations.

With 96 million monthly users, WhatsApp is Russia’s most popular platform, followed by Telegram with 89 million. Past clashes include Russia’s failed Attempt to ban Telegram (2018–20) and Meta’s designation as an extremist entity in 2022.

WhatsApp accused Russia of trying to block encrypted communication and vowed to keep it available. Lawmaker Anton Gorelkin suggested that MAX should replace WhatsApp. The app’s terms permit data sharing with authorities and require pre-installation on all smartphones sold in Russia.

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Musk–Altman clash escalates over Apple’s alleged AI bias

Elon Musk has accused Apple of favouring ChatGPT on its App Store and threatened legal action, sparking a clash with OpenAI CEO Sam Altman. Musk called Apple’s practices an antitrust violation and vowed to take immediate action through his AI company, xAI.

Critics on X noted rivals like DeepSeek AI and Perplexity AI have topped the App Store this year. Altman called Musk’s claim ‘remarkable’ and accused him of manipulating X. Musk called him a ‘liar’, prompting demands for proof he never altered X’s algorithm.

OpenAI and xAI launched new versions of ChatGPT and Grok, ranked first and fifth among free iPhone apps on Tuesday. Apple, which partnered with OpenAI in 2024 to integrate ChatGPT, did not comment on the matter. Rankings take into account engagement, reviews, and downloads.

The dispute reignites a feud between Musk and OpenAI, which he co-founded but left before the success of ChatGPT. In April, OpenAI accused Musk of attempting to harm the company and establish a rival. Musk launched xAI in 2023 to compete with major players in the AI space.

Chinese startup DeepSeek has disrupted the AI market with cost-efficient models. Since ChatGPT’s 2022 debut, major tech firms have invested billions in AI. OpenAI claims Musk’s actions are driven by ambition rather than a mission for humanity’s benefit.

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