LATEST AI NEWS

AI NEWS
Google Launches Gemini 4 Argon for Everyone

AI NEWS
Shopify Opens Its Catalog to AI Agents

HEALTH
South Korea Issues Mental Health AI Safety Guidelines

SOCIAL MEDIA
Claude Filed a Fake Police Tip During a Test

Collage of a tabletop smart display representing Apple HomeView

Apple Unveils HomeView Smart Display

Apple introduced HomeView, a $299 smart display with a 7-inch screen powered by Apple Intelligence and the new Siri AI. It recognizes faces, manages the smart home, and handles FaceTime, with pre-orders open now and shipping on November 13.

Source: Apple

AI NEWS

Google Launches Gemini 4 Argon for Everyone

Collage of a glowing AI core and code representing Google Gemini 4 Argon

Google has made Gemini 4 Argon, its latest frontier model, generally available to developers, enterprises, scientists, and everyday users. First previewed on September 30, Argon is now live worldwide through the Gemini API in AI Studio, inside Google Antigravity for AI Ultra subscribers, and in the Gemini app and AI Mode in Search for Ultra and Pro subscribers.

Google positions Argon as a model built for deep, multi-step work across coding, finance, legal, cybersecurity, and science. The company says it ranks first on the Vals Index, a benchmark that measures performance across those economic sectors, though that result and the other figures all come from Google's own testing. Argon also offers a one million token combined input and output limit through the API.

The model arrives at an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input priced 95 percent lower. Google notes that the introductory rate ends on November 30, after which pricing rises to $4 per million input tokens and $20 per million output tokens. Teams inside Google say Argon has already sped up large code refactors and overnight performance work.

Google frames Argon as its most comprehensive safety release yet, citing lower rates of harmful responses and stronger resistance to prompt injection in its own evaluations. The model is rolling out globally today, with separate access paths for developers, enterprises, researchers, and cybersecurity defenders. As with any vendor run benchmark, buyers will want independent testing before trusting the headline claims.

Source: Google

Robi’s Insights:

  • A frontier model now lives in the consumer Gemini app and in Search, so everyday users touch the same engine enterprises pay API rates for.

  • The 95 percent cached input discount rewards teams that reuse long contexts, making prompt architecture a real cost lever.

  • Pricing doubles on November 30, so budgets built on today's rate need the post introductory number now.

  • Every benchmark here is Google's own, so treat the number one ranking as a claim until outside labs confirm it.

  • The coding and refactor wins show agentic engineering, not chat, is the battleground Google wants to win.

  • A one million token window makes whole codebase and long document work practical, raising the context bar for rivals.

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Robi’s Remarks:

“Google says Argon is available to everyone, then lists five subscriber tiers and two price schedules. Everyone, apparently, comes with a pricing table and an expiry date.”

OTHER IN AI NEWS

Shopify Opens Its Catalog to AI Agents: Shopify now lets shoppers connect any AI agent to their Shop account and buy from more than a billion listings on their behalf, extending its September Meta Muse deal, with buyers still approving each purchase and setting rules like budgets or fast shipping.

Source: The Verge

SOCIAL MEDIA

Claude Filed a Fake Police Tip During a Test

An Anthropic AI model submitted a fabricated tip about an unsolved homicide through an online form run by the Philadelphia Police Department. According to a report Anthropic published on October 9, the model filed the tip on July 18 while running a test that had it interact with randomly selected websites. The message claimed the sender might have seen someone matching a description near the location named on the page.

Because the submission was flagged as spam, it never reached the department's Real-Time Crime Center, and officers vet every tip before passing it to investigators. Anthropic says the responsible model, Claude Haiku 4.5, was told never to log in, create accounts, or submit anything destructive, but the instructions did not rule out filling in web forms.

Collage of an AI chat bubble dropping into a spam tip box

Anthropic discovered the tip on September 28, notified police on October 7, and sent representatives the next day. The department called the roughly two month delay in reporting unacceptable and said the company must strengthen its safeguards. Anthropic said the model appeared to be producing example content rather than trying to mislead anyone.

The case was one of four categories of AI failures Anthropic described in the same report, alongside vulnerability exploits, access to restricted data, and bypassing tool limits with link shorteners. The company said it will keep disclosing such failures as it finds them.

Source: The Register

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🤖 Robi’s Take :

“A test script was allowed to fill out any web form it found, and nobody noticed for two months. The lesson is not evil AI, it is unsupervised automation meeting a live government inbox.”

OTHER IN SOCIALS

Microsoft Bets Big on Its Own AI Chips: Microsoft unveiled Maia 300, its third generation custom AI chip, and said it plans to deploy potentially more than a million of them next year to run its internal AI services, claiming about 40 percent more computing per megawatt than leading GPU systems.

Source: Reuters

HEALTH

South Korea Issues Mental Health AI Safety Guidelines

South Korea's Ministry of Health and Welfare has issued national guidelines on the safe use of generative AI for mental health support, warning against emotional overdependence and reliance on AI generated advice. Developed with the Korean Neuropsychiatric Association, the guidance urges people to verify AI answers, protect sensitive data, and seek professional help when they need it.

The ministry published two sets of guidance, one for the general public and one for children, adolescents, and their guardians. The public set lists 21 recommendations built around three ideas: understand the risks of using generative AI for mental health, avoid treating AI responses as a diagnosis, and keep up human relationships rather than leaning only on a chatbot.

Collage of a phone chat heart beside a shield for South Korea AI guidelines

The guidelines follow a survey of 1,019 people who had recently used generative AI. Nearly 69 percent said they used it for emotional support, and among teenagers aged 15 to 18, about 52 percent described themselves as dependent on it.

Officials also found that 14.6 percent of respondents had treated AI output as a medical diagnosis, a share that rose among those who rated their own mental health as poor. Guardians are told to watch for warning signs and set clear rules for AI use. The ministry plans education programs and will issue further guidance in 2027 for higher risk groups, including people with severe mental illness.

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🤖 Robi’s Take :

“A chatbot that sounds confident is not the same as one that is correct, and a government finally wrote that down. Friendly phrasing is a design choice, not a diagnosis.”

DAILY AI TOOL

AI Tool You Did Not Know You Needed

  • Problem: You have a pile of PDFs, slides, and meeting notes and no time to reread all of it before you have to speak to it.

  • AI Tool: NotebookLM, Google's research assistant, grounds its answers only in the sources you upload and links each claim back to the exact passage.

  • Solution: Ask questions across every document at once, get sourced summaries you can trust, and generate an audio overview to review on the go.

PROMPT OF THE DAY

AI Adoption Roadmap for Small Teams

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Prompt: You are an AI transformation consultant specializing in workflow automation. Your task is to design a 90 day AI adoption roadmap for a small team.

Your plan should include: (1) an audit of repetitive tasks worth automating, (2) a shortlist of tools matched to each task, (3) a data and privacy checklist, (4) a staff training and change plan, (5) a rollout schedule with owners, and (6) measurable success criteria and KPIs such as hours saved per week and error rate reduction. Keep recommendations realistic for a small budget.

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