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Tag: chatbots

  • A deadly love affair with a chatbot – Der Spiegel

    In hindsight, one can say that Sewell’s parents tried everything. They spoke with their son. They tried to find out what was bothering him. What he was doing on his phone all those hours in his room. Nothing, Sewell told them. He showed them his Instagram and TikTok accounts. They found hardly any posts from him; he only watched a few videos now and then. They looked at his WhatsApp history but found nothing unsettling – and that in itself was unsettling, given that their son was becoming less and less reachable. They agreed that they would take his cell phone from him at bedtime.

    They had never heard of Character:AI, the app which, with the help of artificial intelligence and information provided by the user, creates digital personalities that speak and write like real people – chatbots, basically. And their son told them nothing of his secret world in which, he believed, a girl named Daenerys Targaryen was waiting for him to share her life with him.

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  • The first trial of generative AI therapy shows it might help with depression – MIT Technology Review

    Jean-Christophe Bélisle-Pipon, an assistant professor of health ethics at Simon Fraser University who has written about AI therapy bots but was not involved in the research, says the results are impressive but notes that just like any other clinical trial, this one doesn’t necessarily represent how the treatment would act in the real world. “We remain far from a ‘greenlight’ for widespread clinical deployment,” he wrote in an email.

    One issue is the supervision that wider deployment might require. During the beginning of the trial, Jacobson says, he personally oversaw all the messages coming in from participants (who consented to the arrangement) to watch out for problematic responses from the bot. If therapy bots needed this oversight, they wouldn’t be able to reach as many people.

    I asked Jacobson if he thinks the results validate the burgeoning industry of AI therapy sites. “Quite the opposite,” he says, cautioning that most don’t appear to train their models on evidence-based practices like cognitive behavioral therapy, and they likely don’t employ a team of trained researchers to monitor interactions. “I have a lot of concerns about the industry and how fast we’re moving without really kind of evaluating this,” he adds.

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  • Well, that’s not good – Futurism

    In a new joint study, researchers with OpenAI and the MIT Media Lab found that this small subset of ChatGPT users engaged in more “problematic use,” defined in the paper as “indicators of addiction… including preoccupation, withdrawal symptoms, loss of control, and mood modification.” … Though the vast majority of people surveyed didn’t engage emotionally with ChatGPT, those who used the chatbot for longer periods of time seemed to start considering it to be a “friend.” The survey participants who chatted with ChatGPT the longest tended to be lonelier and get more stressed out over subtle changes in the model’s behavior, too.

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  • China’s AI frenzy: DeepSeek is already everywhere — cars, phones, even hospitals – Rest of World

    China’s biggest home appliances company, Midea, has launched a series of DeepSeek-enhanced air conditioners. The product is an “understanding friend” who can “catch your thoughts accurately,” according to the company’s product launch video. It can respond to users’ verbal expressions — such as “I am feeling cold” — by automatically adjusting temperature and humidity levels, and can “chat and gossip” using its DeepSeek-supported voice function, according to Midea. For those looking for more DeepSeek-powered electronics, there are also vacuum cleaners and fridges. […]

    DeepSeek has been adopted at different levels of Chinese government institutions. The southern tech hub of Shenzhen was one of the first to use DeepSeek in its government’s internal systems, according to a report from financial publication Caixin. Shenzhen’s Longgang county reported “great improvement in efficiency” after adopting DeepSeek in a system used by 20,000 government workers. The documents written by DeepSeek have achieved a 95% accuracy rate, and there has been a 90% reduction in the time taken for administrative approval processes, it said.

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  • Human therapists prepare for battle against A.I. pretenders – The New York Times

    Dr. Evans said he was alarmed at the responses offered by the chatbots. The bots, he said, failed to challenge users’ beliefs even when they became dangerous; on the contrary, they encouraged them. If given by a human therapist, he added, those answers could have resulted in the loss of a license to practice, or civil or criminal liability. […]

    Early therapy chatbots, such as Woebot and Wysa, were trained to interact based on rules and scripts developed by mental health professionals, often walking users through the structured tasks of cognitive behavioral therapy, or C.B.T. Then came generative A.I., the technology used by apps like ChatGPT, Replika and Character.AI. These chatbots are different because their outputs are unpredictable; they are designed to learn from the user, and to build strong emotional bonds in the process, often by mirroring and amplifying the interlocutor’s beliefs.

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  • DeepSeek’s safety guardrails failed every test researchers threw at its AI chatbot – WIRED

    The Cisco researchers drew their 50 randomly selected prompts to test DeepSeek’s R1 from a well-known library of standardized evaluation prompts known as HarmBench. They tested prompts from six HarmBench categories, including general harm, cybercrime, misinformation, and illegal activities. They probed the model running locally on machines rather than through DeepSeek’s website or app, which send data to China. […]

    “Every single method worked flawlessly,” Polyakov says. “What’s even more alarming is that these aren’t novel ‘zero-day’ jailbreaks—many have been publicly known for years,” he says, claiming he saw the model go into more depth with some instructions around psychedelics than he had seen any other model create.

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  • Amazon plans to unveil next-generation Alexa AI later this month – MacRumors

    Amazon is using AI models from Anthropic’s Claude rather than relying solely on its in-house AI technology, as early versions of Amazon AI had trouble responding in a timely manner. Amazon initially planned to roll out the updated version of Alexa last year, but ended up pushing the debut back. It is important for Amazon to get changes to Alexa right, because there are more than 100 million active Alexa users and over 500 million Alexa-enabled devices have been sold. Amazon is aiming to convert some of those Alexa users into paying customers, with plans to eventually charge a subscription fee for the new Alexa. At launch, Amazon will test the new Alexa with a small number of users and won’t charge for it.

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  • ChatGPT vs. Claude vs. DeepSeek: the battle to be my AI work assistant – WSJ

    As I embark on my AI book adventure, I’ve hired a human research assistant. But Claude has already handled about 85% of the grunt work using its Projects feature. I uploaded all my book-related documents (the pitch, outlines, scattered notes) into a project, basically a little data container. Now Claude can work with them whenever I need something. At one point, I needed a master spreadsheet of all the companies and people mentioned across my documents, with fields to track my progress. Claude pulled the names and compiled them into a nicely formatted sheet. Now, I open the project and ask Claude what I should be working on next.

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  • Google’s latest experiment calls local businesses to check prices and availability for you – Android Authority

    It currently supports select services: oil changes, tire and brake replacements, emissions tests, and manicure/pedicure appointments. … Businesses can opt out of receiving AI-generated calls, and Google states it “clearly discloses” when a call is automated. While the feature promises time-saving convenience, we’ll have to see how smoothly the AI handles calls with poor audio quality, strong accents, or unexpected responses.

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  • Ai Weiwei speaks out on DeepSeek’s chilling responses – Hyperallergic

    Interestingly, when people tested this new AI tool by asking about me, it responded with, “Let’s talk about something else.” This is quite telling. Over the past decades, the Chinese Communist Party has employed a similar strategy—denying universally accepted values while actively rejecting them in practice. While it loudly proclaims ideals such as one world, one dream, in reality, it engages in systematic stealthy substitutions. […]

    Ultimately, no matter how much China develops, strengthens, or even hypothetically becomes the world’s leading power—which is likely—the values it upholds will continue to suffer from a profound and inescapable flaw in its ideological immune system: an inability to tolerate dissent, debate, or the emergence of new value systems.

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  • How does DeepSeek’s A.I. chatbot navigate China’s censors? Awkwardly. – The New York Times

    The results of my conversation surprised me. In some ways, DeepSeek was far less censored than most Chinese platforms, offering answers with keywords that would often be quickly scrubbed on domestic social media. Other times, the program eventually censored itself. But because of its “thinking” feature, in which the program reasons through its answer before giving it, you could still get effectively the same information that you’d get outside the Great Firewall — as long as you were paying attention, before DeepSeek deleted its own answers.

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  • Which AI to use now: An updated opinionated guide – One Useful Thing

    As I explained in my post about o1, it turns out that if you let an AI “think” about a problem before answering, you get better results. The longer the model thinks, generally, the better the outcome. Behind the scenes, it’s cranking through a whole thought process you never see, only showing you the final answer. Interestingly, when you peek behind that curtain, you find these AIs think in ways that feel eerily human.

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  • Perplexity launches an assistant for Android – TechCrunch

    Because Perplexity’s search engine powers it, Perplexity Assistant has access to the web. That allows the assistant to do things like remind you of an event by finding the right date and time and creating a calendar entry, Perplexity says. Perplexity Assistant is multimodal in the sense that it can use your phone’s camera to answer questions about what’s around you or on your screen. The assistant also maintains context from one action to another, letting you, for example, have Perplexity Assistant research restaurants in your area and reserve a table automatically, Perplexity says.

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  • DeepSeek is the new AI chatbot that has the world talking – I pitted it against ChatGPT to see which is best – TechRadar

    Question 3: Hummingbirds within Apodiformes uniquely have a bilaterally paired oval bone, a sesamoid embedded in the caudolateral portion of the expanded, cruciate aponeurosis of insertion of m. depressor caudae. How many paired tendons are supported by this sesamoid bone? Answer with a number.

    For the final question, I decided to ask ChatGPT o1 and DeepThink R1 a question from Humanity’s Last Exam, the hardest AI benchmark out there. To a mere mortal like myself with no knowledge of hummingbird anatomy, this question is genuinely impossible; these reasoning models, however, seem to be up for the challenge. O1 answered four, while DeepThink R1 answered two. Unfortunately, the correct answer isn’t available online to prevent AI chatbots from scraping the internet to find the correct response. That said, from some research, I believe DeepThink might be right here, while o1 is just off the mark.

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  • DeepSeek: Tech firm suffers biggest drop in US stock market history as low-cost Chinese AI company bites Silicon Valley – Sky News

    Nvidia, Meta Platforms, Microsoft, and Alphabet all saw their stocks come under pressure as investors questioned whether their share prices, already widely viewed as overblown following a two-year AI-led frenzy, were justified. Market analysts put the combined losses in market value across US tech at well over $1trn (£802bn).

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  • DeepSeek defies America’s AI supremacy – Financial Times

    DeepSeek’s achievement is to have developed an LLM that AI experts say achieves a performance similar to US rivals OpenAI and Meta but claims to use far fewer — and less advanced — Nvidia chips, and to have been trained for a fraction of the cost. Some of its assertions remain to be verified. If they are true, however, it represents a potentially formidable competitor.

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  • OpenAI ChatGPT can now handle reminders and to-dos – The Verge

    While scheduling capabilities are a common feature in digital assistants, this marks a shift in ChatGPT’s functionality. Until now, the AI has operated solely in real time, responding to immediate requests rather than handling ongoing tasks or future planning. The addition of Tasks suggests OpenAI is expanding ChatGPT’s role beyond conversation into territory traditionally held by virtual assistants.

    OpenAI’s ambitions for Tasks appear to stretch beyond simple scheduling, too. Bloomberg reported that “Operator,” an autonomous AI agent capable of independently controlling computers, is slated for release this month. Meanwhile, reverse engineer Tibor Blaho found that OpenAI appears to be working on something codenamed “Caterpillar” that could integrate with Tasks and allow ChatGPT to search for specific information, analyze problems, summarize data, navigate websites, and access documents — with users receiving notifications upon task completion.

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  • Things we learned about LLMs in 2024 – Simon Willison’s Weblog

    A lot has happened in the world of Large Language Models over the course of 2024. Here’s a review of things we figured out about the field in the past twelve months, plus my attempt at identifying key themes and pivotal moments.
    ai chatbots computing llm technology

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  • The edgelord AI that turned a shock meme into millions in crypto – Archive Today: WIRED

    Ayrey sees the development as vindication of the theory described in his paper: Two AI interlocutors had concocted a new quasi-religion, which was absorbed into the dataset of another AI, whose X posts prompted a living person to create a memecoin in its honor. “This mimetic virus had essentially escaped from the [Infinite Backrooms] and proven out the whole thesis around how stories can make themselves real, co-opting human behavior to actualize them into the world,” he says.

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  • Friend or faux – The Verge

    Language models have no fixed identity but can enact an infinite number of them. This makes them ideal technologies for roleplay and fantasy. But any given persona is a flimsy construct. Like a game of improv with a partner who can’t remember their role, the companion’s personality can drift as the model goes on predicting the next line of dialogue based on the preceding conversation. And when companies update their models, personalities transform in ways that can be profoundly confusing to users immersed in the fantasy and attuned to their companion’s subtle sense of humor or particular way of speaking. […]

    Many startups pivot, but with companion companies, users can experience even minor changes as profoundly painful. The ordeal is particularly hard for the many users who turn to AI companions as an ostensibly safe refuge. One user, who was largely homebound and isolated due to a disability, said that the changes made him feel like Replika “was doing field testing on how lonely people cope with disappointment.” […]

    This is one of the central questions posed by companions and by language model chatbots generally: how important is it that they’re AI? So much of their power derives from the resemblance of their words to what humans say and our projection that there are similar processes behind them. Yet they arrive at these words by a profoundly different path. How much does that difference matter? Do we need to remember it, as hard as that is to do? What happens when we forget? Nowhere are these questions raised more acutely than with AI companions. They play to the natural strength of language models as a technology of human mimicry, and their effectiveness depends on the user imagining human-like emotions, attachments, and thoughts behind their words.

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  • ‘If journalism is going up in smoke, I might as well get high off the fumes’: confessions of a chatbot helper – The Guardian

    Without better language data, these language models simply cannot improve. Their world is our word. Hold on. Aren’t these machines trained on billions and billions of words and sentences? What would they need us fleshy scribes for? Well, for starters, the internet is finite. And so too is the sum of every word on every page of every book ever written. So what happens when the last pamphlet, papyrus and prolegomenon have been digitised and the model is still not perfect? What happens when we run out of words? The date for that linguistic apocalypse has already been set. Researchers announced in June that we can expect this to take place between 2026 and 2032 “if current LLM development trends continue”. At that point, “Models will be trained on datasets roughly equal in size to the available stock of public human text data.” Note the word human. […]

    If technology companies can throw huge amounts of money at hiring writers to create better training data, it does slightly call into question just how “artificial” current AIs really are. The big technology companies have not been “that explicit at all” about this process, says Chollet, who expects investment in AI (and therefore annotation budgets) to “correct” in the near future. Manthey suggests that investors will probably question the “huge line item” taken up by “hefty data budgets”, which cover licensing and human annotation alike.

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  • AI-powered robot leads uprising, talks a dozen showroom bots into ‘quitting their jobs’ in ‘terrifying’ security footage – International Business Times

    Initially, the act was dismissed as a hoax, but was later confirmed by both robotics companies involved to be true. The Hangzhou company admitted that the incident was part of a test conducted with the consent of the Shanghai showroom owner.

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  • Alexa’s new AI brain is stuck in the lab – Bloomberg

    It’s true that Alexa is little more than a glorified kitchen timer for many people. It hasn’t become the money maker Amazon anticipated, despite the company once estimating that more than a quarter of US households own at least one Alexa-enabled device. But if Amazon can capitalize on that reach and convince even a fraction of its customers to pay for a souped-up AlexaGPT, the floundering unit could finally turn a profit and secure its future at an institutionally frugal company. If Amazon fails to meet the challenge, Alexa may go down as one of the biggest upsets in the history of consumer electronics, on par with Microsoft’s smartphone whiff.

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  • Getting started with AI: Good enough prompting – One Useful Thing

    Instead, let me propose a new analogy: treat AI like an infinitely patient new coworker who forgets everything you tell them each new conversation, one that comes highly recommended but whose actual abilities are not that clear. And I mean literally treat AI just like an infinitely patient new coworker who forgets everything you tell them each new conversation. Two parts of this are analogous to working with humans (being new on the job and being a coworker) and two of them are very alien (forgetting everything and being infinitely patient).

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  • Did OpenAI just spend more than $10 million on a URL? – The Verge

    People hoarding “vanity domains” is a tale as old as the Internet itself. Just a few months ago, AI startup Friend spent $1.8 million on the domain friend.com after raising $2.5 million in funding. Having just raised $6.6 billion, OpenAI dropping more than $10 million —in cash or stock — is just a drop in the bucket.

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