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Tag: artificial-intelligence

  • Legal AI startup Legora hits $5.6 valuation and its battle with Harvey just got hotter

    Anna Heim

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    Concatena says

    Our Take: We’re seeing more “market froth” more than “proven change in legal practice.” Valuations, ad campaigns and celebrity endorsements are racing ahead of most firms’ ability to use these tools in a meaningful way. Right now, the gap between the hype and what fee-earners actually do with Harvey/Legora in a normal Tuesday is still pretty stark. I’d love to hear your experience!

    Your Takeaway: Treat this as a signal to experiment deliberately, not to panic-buy a platform. If you haven’t already, pick one or two contained use cases (e.g. first-draft research notes, clause comparison) and run small, supervised pilots with clear guardrails. Then share honest internal feedback — including the “confused faces” — so you don’t let marketing headlines set your AI strategy.

    Legora is a legal AI startup valued at $5.6 billion and backed by Nvidia and other investors. It competes closely with Harvey, another legal AI company valued at $11 billion, as both expand globally. The rivalry is intense, with big marketing efforts and a focus on applying AI to reshape the legal industry.

    Highlights

    Alongside Atlassian and other new financial investors, NVentures joined Legora’s cap table as part of a $50 million Series D extension that comes a month after the startup’s $550 million Series D.

    Leveraging AI to help lawyers streamline their work, the Swedish-born legal tech startup is competing with U.S. player Harvey.

    Nvidia has laid a new brick in its AI empire. NVentures, its corporate VC fund, has backed Legora, reportedly its first legal AI investment.

  • Firefox maker torches Google for building Prompt API into browser

    Thomas Claburn

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    Concatena says

    Our Take: Mozilla is right to flag real risks with Google’s Prompt API: it bundles a vendor-specific model and policy into a browser API, which can push developers to change the way they build.

    Your Takeaway: There is a very real risk for everyone of AI being built in by the back door even if a product doesn’t appear to use AI. Due diligence in software is getting very difficult.

    Treat any browser‑provided AI API as a potential vector for vendor lock‑in and unexpected content controls; push for neutral, implementable standards that separate API mechanics from any single model or provider policy, test real performance and harms before adoption, and avoid building critical product flows that depend on Chrome‑specific AI behaviour.

    Mozilla opposes Google’s new Prompt API because it may limit web openness and favor Google’s AI model. They worry it forces developers to follow Google’s rules, hurting fairness and interoperability. Google says the API encourages innovation, but tests show its AI often performs poorly.

    Highlights

    "The core problem is interoperability," he said. "Prompts are tightly coupled to models; developers will inevitably tune to the quirks and policies of whatever model they’re building against.

    "This seems like a bad direction for an API on the web platform, and sets a worrying precedent for more APIs that have [browser]-specific rules around usage," he said.

    Perhaps more significantly, Archibald notes that using the Prompt API requires agreeing to Google’s Generative AI Prohibited Uses Policy, which prohibits activities that are not necessarily illegal, like generating "disturbing" content.

    First, he worries that Google’s own Nano model will become the default and that developers will standardize on it in an effort to make the non-deterministic responses of an AI model more predictable. That tendency, he argues, will create pressure for Apple and Mozilla to license Nano, for the sake of a common user experience.

    Mozilla’s concern, as articulated by Archibald, has to do with what the Prompt API means for the web, not to mention Google’s justification for deployment.

    Various vendors like OpenAI and Perplexity have shipped browsers that embed access to remotely hosted AI models. Mozilla itself is testing an AI-based Smart Window in Firefox and it’s developing tools for AI model scaffolding.

    The Prompt API, as Google describes it, "gives web pages the ability to directly prompt a browser-provided language model." It provides a way to send natural language instructions to Google’s Gemini Nano model, which is small enough to be downloaded for local inference through Chrome.

    "We continue to oppose this API, and feel it has severe negative consequences to the interoperability, updatability, and neutrality of the web platform," said Archibald.

    Jake Archibald, Mozilla web developer relations lead, articulated the org’s concerns in a GitHub discussion of the API, which provides a standard way to send and receive prompts and responses from a local machine learning model.

  • White House presses tech companies for support on AI-driven cyberattacks

    Aaron Mak, John Sakellariadis, Dana Nickel

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    Concatena says

    Our Take: Does the approach taken to law making by governments rely a little too much on input from those who perhaps ought to be restricted by the laws that are made? This is a pivotal moment: policymakers want operational help fast, but firms want clear bounds on data sharing, liability and commercial secrecy.

    Your Takeaway: If you work with or run tech/security businesses, be ready to engage but insist on narrow, well‑justified requests, explicit protections for sensitive operational details, and clarity on how shared information will be used and protected; consider tightening disclosure policies and seeking confidentiality or legal safeguards before responding.

    Tech and cyber companies were sent questions about artificial intelligence-led cybersecurity threats, including those posed by Anthropic’s advanced AI model, Mythos.

    Highlights

    The White House has been taking steps to defuse a monthslong legal battle with Anthropic over the company’s efforts to set ethical limits on government use of AI — a fight that led President Donald Trump in February to ban all federal agencies from using the AI company’s software. Since then, growing awareness of Mythos’ cyber prowess — as well as concerns that unauthorized users might be commandeering technology — has agencies clamoring for access to the tool.

    One list of questions sent by the White House to some tech and cyber firms, obtained by POLITICO, covers a range of technical and policy considerations, including which widely used coding projects should be prioritized and more basic questions about how the public and private sectors can work together on initiatives such as Project Glasswing. One question simply asks: “What is the most effective role for the government?”

    The request for additional, detailed information from these companies reflects the intensifying focus in Washington on the evolving threat that hyper-advanced AI tools may pose to national security and digital infrastructure.

    The questions, from the White House’s Office of the National Cyber Director, focus on how specific sectors in the tech and cybersecurity industries can work with the White House to boost their defenses with AI, these people said. Companies have been asked to respond to them by Friday.

    The White House has asked a group of tech companies to answer a set of questions this week about how to ward off digital attacks that frontier AI tools could soon enable, according to four people with knowledge of discussions between the administration and the tech sector.

  • Will AI lead to more accurate opinion polls?

    BBC News – Business

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    Concatena says

    Our Take: Whether about polling or anything else, 90% accuracy sounds like a big number, but in practice it means getting a lot of things wrong. It’s really important when companies cite these kinds of figures to try to get access to real life examples of that margin of error.

    Your Takeaway: Never take accuracy figures on face value – work out what they actually mean.

    It’s cheaper and faster to collect people’s opinions using AI, but will it make polls more accurate?

    Highlights

    One checks he’s answering the question, one analyses whether he’s being too superficial and needs prompting to go deeper, while the third checks that the respondent is not a fraud… not a robot, for example.

    Note: How long will it be before there are products to answer these kinds of calls for you?

    The voice is young, female, brisk and business-like and belongs to an AI agent. A computer programme in other words. A string of code.

    Note: It’s worth questioning why AI agents are so frequently expressed as being female…

    The company claims its method is "10 times faster, 10 times cheaper and 90% as accurate as human polling".

    It does not focus on quantitative polling, which is already largely automated through mass surveys. Instead, it emphasises depth. "We don’t ask people to tick boxes – they have a conversation with an AI," Fontaine explains. "That means we can explore not just what people think, but how they think – how they build their opinions, and even when those opinions change."

  • OpenAI explains why ChatGPT developed a goblin fixation, and how it solved the issue

    Zac Hall

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    Concatena says

    Our Take: LLMs really do latch onto patterns: OpenAI’s “goblin phase” is a silly example of a serious point – the way you train and reward a model can create odd, persistent behaviours that aren’t obvious from the outside. Model outputs are shaped by hidden system prompts and RL tweaks, not just “the law” or “the facts” you put in.

    Your Takeaway: If you’re using LLMs in your business, assume they’ll exaggerate any incentive or pattern you bake in, sometimes in unexpected ways. Treat prompts and “personalities” like configuration, not colour – document them, review them, and stop anthropomorphising them…

    OpenAI noticed that ChatGPT kept talking too much about goblins and other mythical creatures. This happened because of a past feature that rewarded creative use of such metaphors. To fix it, they told the new GPT-5.5 model not to mention these creatures unless really needed.

    Highlights

    Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it is absolutely and unambiguously relevant to the user’s query

    The fix, in part, is a specific set of instructions to never talk about goblins unless it’s abundantly relevant:

    The goblin problem links back to the “Nerdy personality” option briefly supported by ChatGPT.

    To develop the personality, OpenAI needed to “reward” the model to incentivize its creative use of mythical metaphors. However, even after the Nerdy personality option was retired, the model remained unreasonably attached to gremlins, goblins, and other make-believe creatures.