ElevenLabs co‑founder and CEO Mati Staniszewski told attendees at the Web Summit that voice is poised to become the primary way people interact with artificial‑intelligence systems. He highlighted recent advances that let voice models convey emotion and work alongside large language models, and outlined the company’s push toward hybrid cloud‑and‑device processing for wearables and other hardware. Staniszewski also noted partnerships with Meta and warned that deeper voice integration raises privacy and surveillance concerns. Leer más →

AI browsers integrate large language models into the web‑browsing experience, allowing users to ask natural‑language questions, receive summarized answers, and automate tasks such as form‑filling and price comparison. While tools like ChatGPT Atlas, Perplexity's Comet, Microsoft Edge with Copilot, and Brave's Leo promise greater efficiency, they also raise security concerns, including prompt‑injection attacks, data leakage, and hallucinated results. Experts warn that the convenience of AI‑driven browsing must be balanced against privacy risks and the potential impact on the creator economy. The technology is still evolving, and its ultimate role will likely complement, rather than replace, traditional search. Leer más →

The way people discover information online is shifting from clicking links to asking large language models for direct answers. Tools like ChatGPT and Perplexity generate responses by synthesizing content from multiple sources, often without sending users to the original pages. This change disrupts traditional click‑based metrics and forces marketers to rethink content strategy, measurement, and optimization for AI visibility. New engineering‑focused approaches are emerging to decode how models retrieve and rank information, offering brands a way to gauge influence in conversations rather than clicks. Leer más →

A new benchmark called APEX-Agents, designed to test AI performance on real-world professional tasks in consulting, investment banking, and law, reveals that current AI models struggle to meet the demands of knowledge work. Researchers from Mercur report that even top-performing models answer only about a quarter of the questions correctly, highlighting challenges in multi-domain reasoning and information retrieval across tools like Slack and Google Drive. The findings suggest that AI is still far from replacing skilled professionals in high‑value roles. Leer más →

Sequoia Capital is set to invest in Anthropic, the AI startup behind the Claude language models, as part of a multi‑billion‑dollar raise led by GIC and Coatue. The deal, valued at over $350 billion, signals a shift in venture‑capital strategy, with Sequoia backing competing AI firms simultaneously. Analysts view the round as a benchmark for private AI valuations and a catalyst for increased global capital flow into the sector, while European stakeholders watch for implications on regional AI ecosystems. Leer más →

DeepSeek, in partnership with Peking University, unveiled Engram, a new training method that separates static memory from computation in large language models. By using hashed N‑gram lookups and a context‑aware gating mechanism, Engram reduces reliance on high‑bandwidth memory (HBM), allowing models to operate efficiently on standard GPU memory while scaling parameter counts. Tests on a 27‑billion‑parameter model showed measurable gains across industry benchmarks, and the approach integrates with existing hardware solutions such as Phison’s SSD‑based accelerators and emerging CXL standards. Engram could ease pressure on costly memory hardware and stabilize DRAM price volatility. Leer más →

A recent overview clarifies several widespread myths about artificial intelligence. It explains that AI models process statistical patterns rather than think like humans, lack true understanding, and cannot read users' unspoken intentions. The piece also highlights that AI inherits biases from its training data and is not inherently objective. Ongoing human involvement remains essential for training, oversight, and improvement. Finally, it stresses that current AI, including large language models, is far from achieving general intelligence and should be viewed as sophisticated autocomplete tools rather than superintelligent systems. Leer más →

Recent experiments show that large language models, particularly OpenAI's ChatGPT, are increasingly capable of tackling complex mathematical problems. Researchers have used the model to solve several open problems from the Erdős collection, with AI contributions credited for moving numerous problems from "open" to "solved." The progress highlights the growing role of AI tools in mathematical research, formal proof verification, and the broader scientific community. Leer más →

Anthropic announced Claude for Healthcare, a suite of AI tools aimed at providers, payers, and patients. Like OpenAI’s ChatGPT Health, the platform can sync health data from phones and wearables without using that data for model training. Claude adds advanced "connectors" to major medical databases such as the CMS Coverage Database, ICD-10, the National Provider Identifier Standard, and PubMed, enabling faster prior‑authorization reviews and research. While industry observers note the risk of hallucination‑prone large language models offering medical advice, both Anthropic and OpenAI caution users to consult qualified healthcare professionals. Leer más →

Google offers only broad SEO guidance, leaving experts to interpret its search algorithm. In an era of volatile traffic and growing AI use, some publishers are experimenting with "bite-sized" content to please large language models. Google officials say this tactic may show short‑term gains in isolated cases but is not a sustainable strategy, as future algorithm updates will favor content written for humans rather than for AI ranking tricks. Leer más →

Researchers from Tsinghua University, the Beijing Institute for General Artificial Intelligence, and Pennsylvania State University have created a system that lets large language models pose challenging Python coding problems for themselves, solve them, and use the outcomes to improve. The approach, called Absolute Zero Reasoner, showed notable gains in coding and reasoning abilities for open‑source models and suggests a new path toward more autonomous AI learning. Leer más →

An extensive collection of artificial intelligence terminology has been compiled, covering foundational concepts, emerging technologies, ethical considerations, and practical applications. The glossary defines everything from basic machine learning ideas to advanced generative models, providing clear explanations for professionals, students, and anyone interested in understanding how AI is integrated into modern products and services. Leer más →

The term "AI" has become a catch‑all phrase that now covers everything from chatbots to medical imaging tools, leading to widespread confusion. Experts such as Vasant Dhar, Rupert Shute, and Thiago Ferreira explain that AI encompasses many distinct technologies, with generative AI dominating public perception while quieter, long‑standing applications remain overlooked. Understanding the different categories—prediction, recognition, autonomous systems, and more—helps clarify what AI actually does and why precise language matters for both consumers and companies. Leer más →

A practical guide walks newcomers through the crowded AI chatbot market, explaining key differences among popular options such as ChatGPT, Claude, Gemini, Copilot and Perplexity. It breaks down core concepts like language models, free versus paid tiers, hallucinations, memory and privacy, helping users match a tool to their needs—whether for everyday writing, deep research or seamless integration with Google or Microsoft suites. Leer más →

Vibe coding lets people without programming experience create functional apps by describing their vision to AI chatbots such as Gemini, ChatGPT, or Claude. The process hinges on picking the right model, offering clear and detailed prompts, and iterating through multiple revisions. While faster models may require more hands‑on editing, advanced “thinking” models handle larger portions of the code automatically. Users must also tackle basic technical choices, test for bugs, and stay open to restarting projects when needed. The approach empowers non‑technical creators to bring ideas to life with minimal code knowledge. Leer más →

A hands‑on comparison of Google’s Gemini 3 Pro and Gemini 2.5 Flash models shows that the higher‑tier model delivers deeper reasoning and smoother code generation for vibe‑coding projects, while the faster model requires more manual prompting and frequent fixes. The experiment highlights trade‑offs between speed and depth, with Gemini 3 Pro generally producing more complete results with fewer iterations. Leer más →

AI coding agents face limits on the amount of code they can process at once, which can quickly consume token or usage limits when large files are fed directly into a language model. To work around these constraints, developers fine‑tune models to generate auxiliary scripts that extract needed data, allowing the agents to operate on smaller, targeted inputs. Techniques such as dynamic context management and context compression let agents summarize past interactions, preserving essential details while discarding redundant information. These approaches enable semi‑autonomous tools like Claude Code and OpenAI Codex to handle complex codebases more efficiently without overwhelming the underlying model. Leer más →

Generative AI tools are evolving from simple chatbots into autonomous agents that can act on a user's behalf. To deliver this functionality, companies are asking for deep access to personal data, devices, and applications. Experts warn that such access creates significant privacy and cybersecurity risks, including data leakage, unauthorized sharing, and new attack vectors. While tech giants see agents as the next wave of productivity, critics highlight the lack of user control and the potential for pervasive data collection, calling for stronger safeguards and opt‑out mechanisms. Leer más →

Researchers tested several large language models on a series of linguistic challenges, including sentence diagramming, recursion, and phonology. One model, OpenAI's o1, succeeded in parsing complex sentences, generating multiple syntactic trees for ambiguous statements, and inferring phonological rules in invented mini‑languages. The findings suggest that AI can perform metalinguistic tasks previously thought exclusive to human linguists, prompting debate about the future capabilities of language models. Leer más →

Vibe coding—using large language models to write software from prompts—offers faster development and broader accessibility, but it also introduces serious security risks. Studies show a significant portion of AI‑generated code contains serious flaws, and attackers can exploit poisoned code libraries to spread vulnerabilities. Experts stress that human oversight, strict code reviews, private sandboxed models, and Zero‑Trust access controls are essential to mitigate these threats while still benefiting from the efficiency of AI‑assisted development. Leer más →