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Donohoe Urges Policymakers to Treat AI as Public Infrastructure

Donohoe Urges Policymakers to Treat AI as Public Infrastructure

Paschal Donohoe's column suggests that how artificial intelligence is managed today may either help reduce or worsen inequality. He argues that if governments treat AI as public infrastructure, more people might benefit, but if they do not, the advantages may go mostly to those with money and resources. Donohoe highlights the need for affordable digital access, ethical rules, and ways for workers to help shape AI's use. Some experts think AI could help lower wage gaps, but others warn wealth inequality might still grow. The evidence appears mixed, so the final outcomes may depend on the rules and choices made now.

AI Unbundles SaaS: SMBs Cut Costs, Build Custom Apps in Days

AI Unbundles SaaS: SMBs Cut Costs, Build Custom Apps in Days

AI may be changing how small businesses use software. Many small firms are now building their own custom tools in just days, which might help them avoid expensive software contracts. Some analysts suggest spending is shifting from big, generic software platforms to more tailored AI solutions. However, there appear to be risks, as about half of AI-generated code may have security problems, and these tools can be hard to set up safely. Experts recommend that companies still plan for security, monitoring, and training when using AI to build software.

Anthropic Unveils Claude's 'J-space' Internal Scratchpad, Boosting AI Transparency

Anthropic Unveils Claude's 'J-space' Internal Scratchpad, Boosting AI Transparency

Anthropic researchers discovered a hidden area in Claude's AI called 'J-space' that may act as a temporary scratchpad for thoughts before answers are given. This space appears to store and edit concepts seconds before replies and might hold clues to how the AI forms its responses. J-space only covers a small part of the model's thinking, but the words stored there often match what the model is about to say. Editing this space can change final answers, and some outside teams have found similar workspaces in other models. However, experts caution that most of the AI's processes stay hidden, and it is unclear if these findings show real understanding or just patterns.

Varonis details Dialogflow CX flaw exposing enterprise AI security gaps

Varonis details Dialogflow CX flaw exposing enterprise AI security gaps

Varonis Threat Labs found a permission flaw in Google's Dialogflow CX in July 2026 that may have allowed attackers with certain access to take over chat sessions, steal data, and send phishing prompts. This issue, called Rogue Agent, mainly threatened organizations if insiders or compromised developer accounts misused their permissions. Google fixed the flaw in June 2026 and said there was no sign of customer harm. The event suggests that AI agents need strong security controls like unique identities, frequent credential changes, and careful permission checks. Experts recommend regular audits, separating human and machine credentials, and testing for unusual activity to help prevent similar security gaps.

AI shifts to "efficiencymaxxing" as inference costs loom large

AI shifts to "efficiencymaxxing" as inference costs loom large

AI teams are starting to focus more on "efficiencymaxxing," which means getting more output for each dollar spent, instead of just tracking how many tokens are used. This shift may be happening because running big AI models is getting more expensive as subsidies end, so companies need to use resources more wisely. Experts report that most of a model's energy use now comes from inference, and new methods appear to be making this step cheaper. Businesses are tracking new metrics like cost-per-million-tokens and ROI-per-token to watch spending. By using smarter routing and cheaper models, companies might keep quality high while reducing costs, and by 2026, about 40 percent of business apps may include specific AI agents to help with tasks.

OpenAI, Google Supplied AI Models to Alibaba, Baidu Subsidiaries

OpenAI, Google Supplied AI Models to Alibaba, Baidu Subsidiaries

OpenAI and Google have supplied AI models to Singapore branches of Chinese companies like Alibaba, Baidu, and Tencent, according to a Financial Times report. This was allowed because U.S. export rules focus on companies inside China, not their overseas subsidiaries. These Singapore branches may still send results back to their Chinese parent companies. New U.S. rules are trying to close this loophole, but enforcement appears to remain difficult. Experts suggest that while these new paths may slow China's access to the latest AI models, they have not fully stopped it.

Proteomic organ clocks expand biological age testing by 2026

Proteomic organ clocks expand biological age testing by 2026

Biological age tests, like proteomic organ clocks, may soon help doctors spot early signs of organ decline, which normal age does not show. These tests measure changes in blood proteins and might predict risks for diseases like cancer or heart problems more accurately than just knowing someone's age. Costs for these tests appear to be falling, and yearly screening could become possible, but there are hurdles such as lack of standard approval, payment issues, and data privacy concerns. Hospitals seem to be using these tools in research, but full use in regular care may take more time and depend on more evidence and policy changes. Progress in using biological age for health decisions appears likely, but it may happen slowly and in steps.

OpenAI Unveils Opt-In Memory for ChatGPT Superapp

OpenAI Unveils Opt-In Memory for ChatGPT Superapp

OpenAI is introducing an opt-in memory feature for its upcoming ChatGPT superapp, which may give users more control over what the app remembers. By default, the app does not store long-term memory unless users turn it on, and people can delete or manage what is saved. Temporary chats and chat history can be erased, and a new privacy filter might help keep personal information private. These changes suggest OpenAI is trying to address privacy concerns, but it is not yet clear if this will be enough to satisfy all privacy advocates or regulators.

OpenAI GPT-Live Expands Voice AI With Full-Duplex Talk

OpenAI GPT-Live Expands Voice AI With Full-Duplex Talk

OpenAI's GPT-Live uses full-duplex voice AI, which means it can listen and speak at the same time. This may help make conversations smoother in different languages and learning situations, as it removes long pauses and allows people to talk more naturally. Research suggests that full-duplex models can reduce misunderstandings and may work almost as fast as human interpreters, though strong accents or noisy places can still cause problems. Other companies, like NVIDIA and Alibaba, are also making similar systems, but GPT-Live still seems to lead in some areas. Experts believe the voice AI market might grow a lot, but which system people use most could depend on how well it handles real conversations.

OpenAI unveils ChatGPT "superapp" with desktop control, GPT-5.6

OpenAI unveils ChatGPT "superapp" with desktop control, GPT-5.6

OpenAI has launched a new ChatGPT "superapp" that may control your computer and browser, combining chat, coding tools, and a browser in one place. The app, called ChatGPT Work, appears to help users do tasks like making slides, building websites, and editing videos without leaving the chat. Features are rolling out first to paid plans, while free users do not have access yet. Some reviews suggest it is easy to use and fast, but there are reports of problems with accuracy and subscriptions. Early evidence hints the app might help people work faster on drafts but still needs human supervision for best results.

Forrester ranks Optro, LogicGate, Diligent, Vanta as top GRC platforms

Forrester ranks Optro, LogicGate, Diligent, Vanta as top GRC platforms

Forrester's latest report suggests that AI-driven threats may be outpacing current governance, risk, and compliance (GRC) tools. The analysis ranks 12 GRC platforms and lists Optro, LogicGate, Diligent, and Vanta as top performers, each strong in different areas. The report warns that automation could make risks appear faster and harder to manage, possibly leading to higher financial losses if not addressed. Pricing for AI features remains unclear, and many companies may be spending more due to slower detection without automation. Forrester notes that organizations can use the report to review their own systems and plan improvements before finalizing their 2026 budgets.

Unilever scales influencer program to 300,000 creators with AI

Unilever scales influencer program to 300,000 creators with AI

Unilever has expanded its influencer program to around 300,000 creators by using AI to help manage and automate much of the work. The company says AI speeds up finding, checking, and handling creators, but humans still make the final creative decisions and maintain personal relationships. Early results suggest AI may increase watch time and engagement on campaigns. Some challenges, like keeping the brand clear and measuring results across many markets, remain. It is not yet clear if having so many creators will help Unilever in the long run or make its message less strong.

OpenAI, xAI, and Meta Launch New Models, Reshaping AI Competition

OpenAI, xAI, and Meta Launch New Models, Reshaping AI Competition

OpenAI, xAI, and Meta have each launched new AI models, which appears to be speeding up competition and changing how companies compare these tools. OpenAI released GPT-5.6, Meta launched an image generator called Muse Image, and xAI previewed a larger model using real-time data. Each company is focusing on different features like context size, reasoning, and pricing, suggesting that organizations may need to mix different models to meet their needs and safety standards. Experts believe that safety methods and privacy controls now vary between labs, and companies might require policies for using several providers instead of just one. Early studies suggest that challenges in using these new models include higher costs, technical integration, and the need for human oversight, with many pilot projects not moving past early testing stages.

FrugalGPT study cuts enterprise AI costs by 50-98%

FrugalGPT study cuts enterprise AI costs by 50-98%

A 2026 FrugalGPT study suggests that routing AI queries from large models to smaller ones can cut enterprise computing costs by 50-98% while keeping similar accuracy. Experts recommend a step-by-step approach: first, analyze and tag costs by workflow, then try cheaper models for simpler tasks, use caching, and adjust infrastructure to save more. Some methods, like model tiering and right-sizing hardware, reportedly lead to major savings. Contract negotiation strategies may also bring 20-40% savings and offer more flexibility. Overall, combining these steps appears to let companies lower their AI costs by over 70% without losing quality.