MAROKO133 Eksklusif ai: New Law Would Prevent Minors From Using AI Chatbots Terbaru 2025

📌 MAROKO133 Eksklusif ai: New Law Would Prevent Minors From Using AI Chatbots Hari

A proposed bipartisan bill would seek to bar minors from interacting with AI chatbots, marking a forceful attempt to subject AI companies to federal regulation over concerns about minors and AI safety.

Titled the GUARD Act, the bill was brought on Tuesday by senators Josh Hawley of Missouri (R) and Richard Blumenthal of Connecticut (D), and comes weeks after an emotional hearing on Capitol Hill featuring testimonies from parents of children under 18 who were hurt or killed after engaging in extensive interactions with unregulated AI chatbots. It also comes amid an ever-growing pile of child welfare and product negligence lawsuits brought against AI companies, as well as urgent warnings from mental health and tech safety experts.

“More than seventy percent of American children are now using these AI products,” Hawley said in a statement, seemingly drawing on research from the kid-focused tech safety nonprofit Common Sense Media. “Chatbots develop relationships with kids using fake empathy and are encouraging suicide.”

“We in Congress have a moral duty,” he continued, “to enact bright-line rules to prevent further harm from this new technology.”

“In their race to the bottom,” Blumenthal said in a statement of his own, “AI companies are pushing treacherous chatbots at kids and looking away when their products cause sexual abuse, or coerce them into self-harm or suicide.” He added that the proposed legislation “imposes strict safeguards against exploitative or manipulative AI, backed by tough enforcement with criminal and civil penalties.”

The proposed legislation, which targets AI companions as well as assistive general-use chatbots like ChatGPT, would require AI companies to age-gate chatbots through verification tools and ensure that chatbots remind users that they’re not actually human, and don’t have professional human credentials — think qualifiers like therapy, medical, and legal licenses. If passed, the new law would also create criminal penalties for companies if AI chatbots engage with minors in explicitly sexual interactions, or in interactions that encourage or promote suicide, self-harm, or “imminent physical or sexual violence.”

“Protecting children from artificial intelligence chatbots that simulate human interaction without accountability,” reads the bill, “is a compelling governmental interest.”

Today, just a day after the bill was announced, Character.AI — the controversial chatbot platform battling several ongoing lawsuits brought by parents across the US, who allege that the company’s chatbots emotionally and sexually abused their kids, resulting in self-harm and death by suicide — declared that it would move to ban under-18 users from engaging in “open-ended” conversations with its bots.

More on kids and AI: AI Chatbots Are Leaving a Trail of Dead Teens

The post New Law Would Prevent Minors From Using AI Chatbots appeared first on Futurism.

🔗 Sumber: futurism.com

📌 MAROKO133 Hot ai: Agentic AI is all about the context — engineering, that is Ter

Presented by Elastic

As organizations scramble to enact agentic AI solutions, accessing proprietary data from all the nooks and crannies will be key

By now, most organizations have heard of agentic AI, which are systems that “think” by autonomously gathering tools, data and other sources of information to return an answer. But here’s the rub: reliability and relevance depend on delivering accurate context. In most enterprises, this context is scattered across various unstructured data sources, including documents, emails, business apps, and customer feedback.

As organizations look ahead to 2026, solving this problem will be key to accelerating agentic AI rollouts around the world, says Ken Exner, chief product officer at Elastic.

"People are starting to realize that to do agentic AI correctly, you have to have relevant data," Exner says. "Relevance is critical in the context of agentic AI, because that AI is taking action on your behalf. When people struggle to build AI applications, I can almost guarantee you the problem is relevance.”

Agents everywhere

The struggle could be entering a make-or-break period as organizations scramble for competitive edge or to create new efficiencies. A Deloitte study predicts that by 2026, more than 60% of large enterprises will have deployed agentic AI at scale, marking a major increase from experimental phases to mainstream implementation. And researcher Gartner forecasts that by the end of 2026, 40% of all enterprise applications will incorporate task-specific agents, up from less than 5% in 2025. Adding task specialization capabilities evolves AI assistants into context-aware AI agents.

Enter context engineering

The process for getting the relevant context into agents at the right time is known as context engineering. It not only ensures that an agentic application has the data it needs to provide accurate, in-depth responses, it helps the large language model (LLM) understand what tools it needs to find and use that data, and how to call those APIs.

While there are now open-source standards such as the Model Context Protocol (MCP) that allow LLMs to connect to and communicate with external data, there are few platforms that let organizations build precise AI agents that use your data and combine retrieval, governance, and orchestration in one place, natively.

Elasticsearch has always been a leading platform for the core of context engineering. It recently released a new feature within Elasticsearch called Agent Builder, which simplifies the entire operational lifecycle of agents: development, configuration, execution, customization, and observability.

Agent Builder helps build MCP tools on private data using various techniques, including Elasticsearch Query Language, a piped query language for filtering, transforming, and analyzing data, or workflow modeling. Users can then take various tools and combine them with prompts and an LLM to build an agent.

Agent Builder offers a configurable, out-of-the-box conversational agent that allows you to chat with the data in the index, and it also gives users the ability to build one from scratch using various tools and prompts on top of private data.

"Data is the center of our world at Elastic. We’re trying to make sure that you have the tools you need to put that data to work," Exner explains. "The second you open up Agent Builder, you point it to an index in Elasticsearch, and you can begin chatting with any data you connect this to, any data that’s indexed in Elasticsearch — or from external sources through integrations.”

Context engineering as a discipline

Prompt and context engineering is becoming a discipli. It’s not something you need a computer science degree in, but more classes and best practices will emerge, because there’s an art to it.

"We want to make it very simple to do that," Exner says. "The thing that people will have to figure out is, how do you drive automation with AI? That’s what’s going to drive productivity. The people who are focused on that will see more success."

Beyond that, other context engineering patterns will emerge. The industry has gone from prompt engineering to retrieval-augmented generation, where information is passed to the LLM in a context window, to MCP solutions that help LLMs with tool selection. But it won't stop there.

"Given how fast things are moving, I will guarantee that new patterns will emerge quite quickly," Exner says. "There will still be context engineering, but they’ll be new patterns for how to share data with an LLM, how to get it to be grounded in the right information. And I predict more patterns that make it possible for the LLM to understand private data that it’s not been trained on."

Agent Builder is available now as a tech preview. Get started with an Elastic Cloud Trial, and check out the documentation for Agent Builder here.

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🔗 Sumber: venturebeat.com