OpenEvidence, a fast-growing start-up, is using artificial intelligence to help doctors find answers to clinical questions for diagnosis and treatment.
Seja na navegação por interface de voz, controlar a música ou fazer chamadas e enviar mensagens, a Siri poderá ser muito útil no automóvel para não largar as mãos do volante.
Et si l’avenir du traitement du cancer passait par des médicaments capables de frapper uniquement les cellules malades ? Plus ciblés, souvent mieux tolérés et porteurs d’espoir face à des tumeurs résistantes, les anticorps conjugués pourraient bouleverser la prise en charge de nombreux cancers.
Selecionadas pela Startup Portugal e pela Unicorn Factory Lisboa, as 27 empresas vêm de sectores como IA, Machine Learning ou Tecnologia da Saúde, empregando mais de 200 pessoas e com investimentos captados superiores a 20 milhões de euros.
SAN FRANCISCO – NewOrbit Space, a UK startup developing satellites for very low Earth orbit (VLEO), has raised $18.5 million in a Series A investment round. With the funding, announced […]
Two Dots assinala o seu 12.º aniversário este ano e é um clássico que vale a pena redescobrir, com quebra-cabeças para ligar pontos coloridos, bem como vários modos de jogo adicionais para explorar.
Com recurso a inteligência artificial, o Toyzie identifica Hot Wheels, figuras de ação, Funko Pops, cartas TCG e muito mais, e diz-lhe, em segundos, o que tem na coleção e quanto vale cada peça no mercado atual.
Indigenous Peoples in Voluntary Isolation and Initial Contact (PIACI) in the Yavarí-Tapiche Territorial Corridor, one of the largest contiguous, intact forests in the Amazon and home to the world’s highest concentrations of PIACI, are under threat by extractive and large-scale industrial activities, which pose an existential threat to its inhabitants and the ecosystems they depend on. This is according to a new report co-authored by Earth Insight, the Regional Organization of Indigenous Peoples of the East (ORPIO), the Coordination of the Indigenous Organizations of the Brazilian Amazon (COIAB) and the Interethnic Association for the Development of the Peruvian Rainforest (AIDESEP). The report finds that oil and gas blocks overlap with 10% of the 16-million-hectare (39.5-million-acre) corridor, including almost 1.7 million hectares (4.2 million acres) of intact tropical moist forest, 907,000 hectares (2.2 million acres) of Key Biodiversity Areas and 713,000 hectares (1.8 million acres) of protected areas. “Pressure from hydrocarbons is increasing on the Peruvian side of the Yavarí Tapiche corridor,” Edith Espejo, senior program manager at Earth Insight and author of the report, told Mongabay over WhatsApp messages. “Our report serves as a warning for the irreversible harm that could take place if these oil blocks move into this corridor. Mining concessions within and on the peripheries of the corridor also pose a threat of encroachment and contamination of waterways.” A critical corridor for ecosystems and Indigenous communities The Yavarí-Tapiche Corridor covers Brazil’s western border states of Amazonas and Acre and Peru’s Loreto and Ucayali departments in the Amazon…This article was originally published on Mongabay
Elon Musk’s rocket company, on the cusp of the largest initial public offering ever, will soon end up in index funds after rule changes by Nasdaq and other index providers.
Et si l'univers avait une date d'expiration bien plus proche que prévu ? Une étude récente bouleverse les certitudes cosmologiques les mieux établies. Le compte à rebours serait lancé : 33 milliards d'années, pas une de plus.
Os planos da Smart Runner ajustam-se automaticamente ao longo do tempo, tendo em conta a evolução dos utilizadores, e, através da integração com o Apple Watch, é possível acompanhar métricas em tempo real durante os treinos.
Google has released new tools that allow developers to run agentic AI workflows locally using Gemma 4 12B, a 12-billion-parameter model from Google DeepMind.
In a blog post, the company said the model, combined with the Google AI Edge stack, can be used to build and test applications on everyday machines. The model-runtime combination supports capabilities such as autonomous data processing, visual insight generation, webpage creation, and tool use.
The release includes Google AI Edge Gallery for macOS, where developers can use Gemma 4 12B to generate and run scripts for tasks such as data analysis. Google also said its Eloquent voice dictation and editing app now runs fully on-device on macOS, with support for local transcription and voice-driven text editing.
Google has also expanded LiteRT-LM, its lightweight command-line tool for running language models locally, with a new serve command. The company said this allows the CLI to act as a local LLM server and lets developers connect Gemma 4 12B to standard tools, SDKs, and frameworks through a local endpoint.
“Your data stays on your device while maintaining reliable responsiveness, utility, and cost efficiency,” the company said in the blog post.
The announcement comes as enterprises are looking beyond large, general-purpose models for some AI workloads. Gartner predicted that by 2027, organizations will use small, task-specific AI models at least three times more than general-purpose large language models, citing demand for more contextualized and cost-effective AI systems.
Challenges to overcome
But running agents on employee devices brings a number of problems. Companies must work within the limits of endpoint hardware, which can restrict the size of models that run effectively and the number of model instances that can operate at one time.
“While the AI can now fit on a laptop, enterprise IT infrastructure is largely unprepared to manage it,” said Rishi Padhi, principal analyst at Gartner. “Even highly optimized models like the Gemma 4 12B require around 16GB of unified memory or VRAM to run alongside standard applications. Many standard-issue enterprise laptops lack the memory bandwidth and NPUs/GPUs required for fluid, multi-turn agentic execution.”
Anand Joshi, AI analyst at TechInsights, said local deployment also changes the nature of the workloads. On a PC, search may mean finding information across internal folders and files. In a data center, the same function could involve searching the internet or querying a large database such as SQL.
“The framework for local deployment of agentic AI is different from that of a data center,” Joshi said. “The models are smaller; you can run only one instance of a large model at a time. You are limited by memory, CPU, and so on.”
Security and governance are also likely to become bigger concerns as AI agents move closer to enterprise endpoints. Agentic AI is designed to take actions, creating new security risks when local models are given access to employee files or allowed to interact directly with applications and scripts.
“Sandboxing these agents without breaking their utility is still a major operational challenge,” Padhi added. “And all this while enterprises need to audit AI usage for compliance and security. When inference happens entirely offline, capturing logs, tracking model drift, and ensuring employees are using the approved, compliant ways for a model becomes incredibly difficult.”
The cost tradeoff
Running AI agents locally could reduce some cloud inference costs, but the savings may be offset in the near term by higher spending on endpoint hardware and management.
“First and foremost, it is an OpEx-to-CapEx shift, as it shifts that financial burden by forcing accelerated hardware refresh cycles for premium PCs or edge devices,” Padhi said. “It would require buying expensive, high-memory laptops for employees at a time when memflation in the hardware industry is already driving up end-user average selling prices for laptops.”
Many enterprises refreshed PCs in 2025 to support Windows 11, but at that point, most AI inference still ran in the cloud, and the case for on-device AI remained unclear, Padhi said.
Enterprises may therefore move cautiously, buying AI-capable PCs only where local inference has a clear business case.
Over time, however, on-device AI could make enterprise AI spending more predictable by reducing exposure to variable cloud inference bills. The tradeoff is that companies may face a higher baseline cost for equipping and managing employees’ devices.
Complementing cloud AI
For enterprises, local AI is unlikely to replace cloud-based AI outright. Analysts said local AI is more likely to be used for workloads that benefit from endpoint processing, especially when applications must operate offline or when privacy and response times are critical.
“For local agentic AI to proliferate, the use cases on edge will have to complement data center/cloud use cases,” Joshi said. “I don’t expect local agentic AI to replace cloud AI, but it has potential to take a slice away from the cloud, and models like Gemma are significant steps towards enabling that.”
The market, Joshi added, is still determining where local AI fits best. “I estimate that use cases that require privacy or have strict latency needs will move to local node first, with further migration of others in the next 2-3 years,” he said.
Padhi said model placement will depend on the privacy requirements of a workload, the computing power it needs, and where the relevant data resides. Tasks such as code generation or analysis of local files could increasingly run on employee devices, while enterprise-wide RAG systems and more complex AI workflows are likely to remain cloud-based.
The $135 share price means Elon Musk’s rocket maker is poised to exceed the 2019 initial public offering of Saudi Aramco in both valuation and money raised.
Com mais de 10 milhões de jogadores em todo o mundo, Airport Simulator: Plane City é um simulador de gestão de aeroportos do estúdio francês Playrion que mistura estratégia, personalização e a calma hipnótica de ver aviões a descolar e a aterrar.
Login
