Artificial intelligence

Artificial intelligence

Everybody would say yes, but we kept moving the goalposts," Ghodsi said in the discussion, which was published Tuesday.

In this week's edition of Computer Weekly, we take a closer look at reports of low workplace morale within the Police Digital Service, as its staff eagerly await the outcome of the long-promised Home Office's policing reform whitepaper. Jérôme Goulard, the chief sustainability officer of Orange Business, talks us through the work he is doing to balance business objectives with IT sustainability within the organisation.

Tesla's Robotaxi service is only available in Austin and the Bay Area for now, but those who have used the service have generally been appreciative of its capabilities and performance. Some Robotaxi customers have observed that the service is simply so much more affordable than Uber, and its driving is actually really good. Perhaps my biggest takeaway from comparing Robotaxi to uber isn't how cheap Robotaxi is... it's how insanely expensive uber has become.

In a new study, Gartner claimed AI will "touch all IT work by 2030" as enterprises ramp up adoption of new tools to drive productivity and alleviate strain placed on stretched IT teams. The extent of AI's influence in IT departments will vary, according to the consultancy. In a survey, CIOs said they expect around 75% of work to be done "by humans augmented with AI" by 2030, while around 25% of tasks will be carried out by AI alone.

In the decades since natural language processing (NLP) first emerged as a research field, artificial intelligence has evolved from a linguistic curiosity into a catalyst reshaping how humans think, work, and create. Few people are as qualified to trace that journey, or to imagine what comes next, as Rada Mihalcea, Professor of Computer Science and Engineering and Director of the Michigan AI Lab at the University of Michigan.

AI inference is the process by which a trained large language model (LLM) applies what it has learned to new data to make predictions, decisions, or classifications. In practical terms, the process goes like this. After a model is trained, say the new GPT 5.1, we use it during the inference phase, where it analyzes data (like a new image) and produces an output (identifying what's in the image) without being explicitly programmed for each fresh image. These inference workloads bridge the gap between LLMs and AI chatbots and agents.

The system combines an ontology model, semantic models, and AI agents to convert business data into real-time decision-making. According to Microsoft, organizations are drowning in data without understanding the semantics. For example, an airline does not think in terms of tables and schedules, but in terms of flights, passengers, and delays. However, that meaning lives in people's minds. Teams use their own definitions and reports. AI systems can read data, but they lack the business context to make reliable decisions.

Soumith Chintala, a former AI leader at Meta and one of the most influential figures in modern AI infrastructure, has joined former OpenAI CTO Mira Murati's startup, Thinking Machines Lab. '[T]hinking machines...the people are incredible,' Chintala posted to his X account on Tuesday. He also updated his X bio and LinkedIn profile to indicate that he is now working at the startup, marking his first move since leaving Meta earlier this month.

Alibaba Cloud is not inherently a security threat, but its ties to China and the legal environment create potential risks that Western companies must carefully evaluate. For low-risk applications (e.g., serving customers in Asia), it may be a viable option. For high-sensitivity operations, most security-conscious organizations opt for cloud providers based in allied countries with strong rule-of-law protections (e.g., AWS, Microsoft Azure, Google Cloud).

As organizations embrace AI agents, they face a rapidly fragmenting landscape. Every SaaS-application is embedding agents, cloudproviders are building agents, partners are building agents, and internal teams are developing their own agentic solutions. This creates new challenges: how do you manage, secure, and observe all these agents working together? How do you keep a clear overview?

Throughout the past few years, I've observed that many people in the marketing world have moved past their initial worries about AI. A common theme I'm hearing these days? It isn't that AI will take over, but rather that we're moving toward incorporation. I see AI as a fast, intuitive tool. But as marketers, how should we use it?

The world's largest online retailer says this amounts to "computer fraud" when not disclosed. The clash between the two companies offers "an early glimpse into a looming debate" over "agentic artificial intelligence." Perplexity is among several tech firms, including Google and OpenAI, racing "to rethink the traditional web browser around AI," with automated agents that can complete tasks like emailing or shopping.

Kumma told us where to find a variety of potentially dangerous objects, including knives, pills, matches, and plastic bags,

IBM attributes those improved characteristics vs. larger models to its hybrid architecture that combines a small amount of standard transformer-style attention layers with a majority of Mamba layers-more specifically, Mamba-2. With 9 Mamba blocks per 1 Transformer block, Granite gets linear scaling vs. context length for the Mamba parts (vs. quadratic scaling in transformers), plus local contextual dependencies from transformer attention (important for in-context learning or few-shots prompting).

Google appears to be preparing for the introduction of Gemini 3.0. The new AI model briefly appeared in AI Studio, the development platform where programmers, researchers, and students work with the various Gemini models. According to BleepingComputer, the fact that the model is now visible there indicates that the official rollout is not far off. The update is expected to go live within a few hours to days.

This is all about deepening our commitment to bringing the best infrastructure, model choice and applications to our customers, Nadella said on a video call with the other two executives, adding that it builds on the critical partnership Microsoft still has with OpenAI.

They wrote something genuine, then passed it through an AI writer of their choice ten times in a row. After each iteration, they rated it on a 1-7 scale: "How much is this still mine?" The survey itself ran on Qualtrics; I cleaned and visualized the data in R, using a simple mixed-effects model to trace how that sense of ownership decayed over time. Everyone consented, all responses were anonymized, and what's shown here reflects only the aggregate picture.

Since prehistoric ages, humans had to decide on whether the place they are in is safe to stay in or not, if the strangers they meet on their way are safe to be around or not, and if the berries they were given by others were safe to eat or not. In psychology, trust is the willingness to rely on someone or something despite uncertainty. In tech, trust means believing that the system is competent, predictable, aligned with your goals, and transparent about limitations.

The launch of ChatGPT by OpenAI in November 2022 marked a turning point in the AI landscape, igniting the broader AI boom. This generative AI tool demonstrated practical applications for everyday users, from content creation to coding assistance, sparking massive public interest and investment. Tech giants poured billions into AI development, while startups flooded the ...