Artificial intelligence

California introduces first AI chatbot safety law

California has become the first US state to regulate AI companion chatbots after Governor Gavin Newsom signed landmark legislation designed to protect children and vulnerable users. The new law, SB 243, holds companies legally accountable if their chatbots fail to meet new safety and transparency standards.

The US legislation follows several tragic cases, including the death of a teenager who reportedly engaged in suicidal conversations with an AI chatbot. It also comes after leaked documents revealed that some AI systems allowed inappropriate exchanges with minors.

Under the new rules, firms must introduce age verification, self-harm prevention protocols, and warnings for users engaging with companion chatbots. Platforms must clearly state that conversations are AI-generated and are barred from presenting chatbots as healthcare professionals.

Major developers including OpenAI, Replika, and Character.AI say they are introducing stronger parental controls, content filters, and crisis support systems to comply. Lawmakers hope the move will inspire other states to adopt similar protections as AI companionship tools become increasingly popular.

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Salesforce invests $15 billion in San Francisco’s AI future

The US cloud-based software company, Salesforce, has announced a $15 billion investment in San Francisco over the next five years, strengthening the city’s position as the world’s AI capital.

The funding will support a new AI Incubator Hub on the company’s campus, workforce training programmes, and initiatives to help businesses transform into ‘Agentic Enterprises’.

A move that coincides with the company’s annual Dreamforce conference, expected to generate $130 million in local revenue and create 35,000 jobs.

Chief Executive Marc Benioff said the investment demonstrates Salesforce’s deep commitment to San Francisco, aiming to boost AI innovation and job creation.

Dreamforce, now in its 23rd year, is the world’s largest AI event, attracting nearly 50,000 participants and millions more online. Benioff described the company’s goal as leading a new technological era where humans and AI collaborate to drive progress and productivity.

Founded in 1999 as an online CRM service, Salesforce has evolved into a global leader in enterprise AI and cloud computing. It is now San Francisco’s largest private employer and continues to expand through acquisitions of local AI firms such as Bluebirds, Waii, and Regrello.

The company’s new AI Incubator Hub will support early-stage startups, while its Trailhead learning platform has already trained more than five million people for the AI-driven workplace.

Salesforce remains one of the city’s most active corporate philanthropists. Its 1-1-1 model has inspired thousands of companies worldwide to dedicate a share of equity, product, and employee time to social causes.

With an additional $39 million pledged to education and healthcare, Salesforce and the Benioffs have now donated over $1 billion to the Bay Area.

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India’s AI infrastructure gets a $15bn lift from Google

Google has announced a $15 billion commitment for 2026–2030 to build its first Indian AI hub in Visakhapatnam, positioning itself as a foundational partner in India’s AI-first push and strengthening US–India tech ties.

The hub will centre on a purpose-built, gigawatt-scale data-centre campus engineered to Google’s global standards for performance, reliability, and low latency. Partners AdaniConnex and Airtel will help deliver enterprise-grade capacity, enabling large companies and startups to build and scale AI-powered services.

Beyond compute, Google will anchor an international subsea gateway in Visakhapatnam, landing multiple cables to complement those in Mumbai and Chennai, adding route diversity, lowering latency across India’s east coast, and strengthening national connectivity for users, developers, and enterprises.

Clean growth is a core pillar of the plan, with work on transmission lines, new clean-energy generation, and storage in Andhra Pradesh. Google will apply its energy-efficient data centre design to expand India’s diverse clean power portfolio while supporting grid reliability and long-term sustainability goals.

The initiative aligns with the Viksit Bharat 2047 vision, targeting high-value jobs in India and spillover benefits to US research and development. By combining compute, connectivity, and clean energy at scale, Google aims to accelerate AI adoption across sectors and broaden digital inclusion nationwide.

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NVIDIA-powered Zora AI pairs with Oracle AI Agent Studio

Deloitte unveils Zora AI, powered by Oracle Fusion and OCI, to automate complex work and cut costs. Built on NVIDIA’s stack with Oracle AI Agent Studio, it delivers sharper, more contextual insights. The pitch: faster execution and fewer handoffs.

Deep-reasoning agents in the Zora AI team with embedded Oracle agents as coordinated multi-agent workflows. Finance, HR, customer experience, and supply chains gain real-time recommendations and error detection at scale. Data siloes give way to decisions on a unified Fusion platform.

Security and scale rely on OCI Generative AI and Oracle’s ‘on by default’ protections with Autonomous Database. NVIDIA NIM and NeMo support building, deploying, and optimising agents in regulated settings. Trustworthy AI principles cover governance, risk, and compliance from day one.

‘By running Zora AI on Oracle’s cloud, we’re unlocking end-to-end efficiencies,’ said Deloitte’s Mauro Schiavon. Oracle’s Roger Barga said Fusion integration will ‘accelerate innovation and future-proof’ investments. NVIDIA’s John Fanelli cited ‘digital workers at scale’ boosting productivity and autonomy.

Early deployments span finance, sourcing, procurement, sales, and marketing. Finance agents collaborate with Fusion SCM to predict disruptions and optimise operations. An enhanced partner programme adds enablement, accelerators, and go-to-market support.

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Microsoft strengthens UAE AI infrastructure

Microsoft has announced a strategic investment to enable in-country data processing for Microsoft 365 Copilot in the UAE. The service will be available to qualified UAE organisations in early 2026, hosted in Microsoft’s Dubai and Abu Dhabi cloud centres for secure, local AI processing.

The move aligns with the UAE’s ambition to become a global AI hub, supported by initiatives such as the National Artificial Intelligence Strategy 2031 and the Dubai Universal Blueprint for AI.

Government leaders emphasise that in-country AI infrastructure strengthens trust, cyber resilience, and innovation across ministries and public entities.

Collaboration with the UAE Cybersecurity Council (CSC) and the Dubai Electronic Security Center (DESC) ensures Microsoft 365 Copilot complies with national AI policies and data governance standards.

Local processing cuts latency, protects data, and supports regulated environments, allowing government stakeholders to adopt AI securely.

Microsoft and its strategic partner G42 International highlight the initiative’s broader impact on the UAE’s digital economy. The project could create 152,000 jobs and train one million UAE learners in AI by 2027, supporting a secure and innovative digital future.

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OpenAI and Broadcom unite to deploy 10 gigawatts of AI accelerators

The US firm, OpenAI, has announced a multi-year collaboration with Broadcom to design and deploy 10 gigawatts of custom AI accelerators.

The partnership will combine OpenAI’s chip design expertise with Broadcom’s networking and Ethernet technologies to create large-scale AI infrastructure. The deployment is expected to begin in the second half of 2026 and be completed by the end of 2029.

A collaboration that enables OpenAI to integrate insights gained from its frontier models directly into the hardware, enhancing efficiency and performance.

Broadcom will develop racks of AI accelerators and networking systems across OpenAI’s data centres and those of its partners. The initiative is expected to meet growing global demand for advanced AI computation.

Executives from both companies described the partnership as a significant step toward the next generation of AI infrastructure. OpenAI CEO Sam Altman said it would help deliver the computing capacity needed to realise the benefits of AI for people and businesses worldwide.

Broadcom CEO Hock Tan called the collaboration a milestone in the industry’s pursuit of more capable and scalable AI systems.

The agreement strengthens Broadcom’s position in AI networking and underlines OpenAI’s move toward greater control of its technological ecosystem. By developing its own accelerators, OpenAI aims to boost innovation while advancing its mission to ensure artificial general intelligence benefits humanity.

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Google gives students free access to AI tools

Google has launched a 12-month free AI Pro Plan for university students aged 18 and above across Europe, the Middle East, and Africa. The plan gives access to Google’s top AI tools, including Gemini 2.5 Pro, Deep Research, NotebookLM, Veo 3, Nano Banana, and 2 TB of cloud storage.

Students can use these tools for homework, research, content creation, and creative projects, all designed to enhance learning and skill development.

Guided Learning in Gemini helps students with step-by-step support for math, essays, and test preparation. AI tools let students explore creativity by generating images, editing visuals, and making short cinematic clips with Veo 3 and Nano Banana.

Educators gain over 30 new tools with Gemini for Education and Classroom to plan lessons, create resources, and foster AI literacy. Google is partnering with universities to integrate AI into teaching, helping students gain practical skills for the future workforce.

The initiative reflects Google’s commitment to equipping students with AI skills, boosting critical thinking, creativity, and problem-solving while expanding access to knowledge through innovative technologies.

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Vodafone and Samsung expand Open RAN deployment across Europe

Samsung Electronics has been chosen by Vodafone as a primary partner to deploy virtualised RAN and Open RAN networks in Germany and several European countries. The agreement builds on previous collaborations and represents one of the largest Open RAN projects in Europe.

Germany will serve as the first and main market, with thousands of sites planned, including a full deployment in Wismar by early 2026. The rollout will expand across Europe over five years, beginning with a live site already operating in Hannover.

Samsung will provide its virtualised RAN solutions supporting 2G, 4G and 5G, as well as O-RAN compliant radios, Massive MIMO equipment and AI-powered management tools. The company will also integrate its CognitiV Network Operations Suite to improve performance, efficiency and automation.

Partners such as Dell Technologies, Intel and Wind River will contribute hardware and cloud platforms to ensure interoperability and large-scale integration.

Vodafone’s Chief Network Officer Alberto Ripepi said Open RAN is essential for building flexible, future-ready networks and expanding connectivity across Europe.

Samsung’s Networks Business President Woojune Kim highlighted the project as a major step in developing software-based and autonomous networks designed for the AI era. Both companies view the partnership as a means to advance digital transformation and enhance network efficiency.

The collaboration also promotes energy efficiency and shared infrastructure. Samsung’s AI Energy Saving Manager will monitor traffic to reduce power consumption during low-use periods. The company’s radio systems will support RAN sharing, helping operators cut costs and deliver consistent coverage.

Analysts consider Vodafone’s decision a validation of Samsung’s leadership in open and virtualised network technology.

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Nvidia DGX Spark launches as the world’s smallest AI supercomputer

Nvidia has launched the DGX Spark, described as the world’s smallest AI supercomputer.

Designed for developers and smaller enterprises, the Spark offers data centre-level performance without the need for costly AI server infrastructure or cloud rentals. It features Nvidia’s GB10 Grace Blackwell superchip, ConnectX-7 networking, and the company’s complete AI software stack.

The system, co-developed with ASUS and Dell, can support up to 128GB of memory, enabling users to train and run substantial AI models locally.

Nvidia CEO Jensen Huang compared Spark’s mission to the 2016 DGX-1, which he delivered to Elon Musk’s OpenAI, marking the start of the AI revolution. The new Spark, he said, aims to place supercomputing power directly in the hands of every developer.

Running on Nvidia’s Linux-based DGX OS, the Spark is built for AI model creation rather than general computing or gaming. Two units can be connected to handle models with up to 405 billion parameters.

The device complements Nvidia’s DGX Station, powered by the more advanced GB300 Grace Blackwell Ultra chip.

Nvidia continues to dominate the AI chip industry through its powerful hardware and CUDA platform, securing multi-billion-dollar deals with companies such as OpenAI, Google, Meta, Microsoft, and Amazon. The DGX Spark reinforces its position by expanding access to AI computing at the desktop level.

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Smartphone AI estimates avocado ripeness with high accuracy

Researchers at Oregon State University and Florida State University have unveiled a smartphone-based AI system that accurately predicts the ripeness and internal quality of avocados.

They trained models using more than 1,400 iPhone images of Hass avocados, achieving around 92% accuracy for firmness (a proxy for ripeness) and over 84% accuracy in distinguishing fresh from rotten fruit.

Avocado waste is a major issue because they spoil quickly, and many are discarded before reaching consumers. The AI tool is intended to guide both shoppers and businesses on when fruit is best consumed or sold.

Beyond consumer use, the system could be deployed in processing and retail facilities to sort avocados more precisely. For example, more ripe batches might be sent to nearby stores instead of longer transit routes.

The researchers used deep learning (rather than older, manual feature extraction) to capture shape, texture and spatial cues better. As the model dataset grows, its performance is expected to improve further.

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