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Imagine sitting across from an AI interviewer, answering questions about your life, preferences, and opinions for two hours. When the session ends, the AI confidently declares it can replicate your personality — answering questions, making decisions, and reacting to situations just like you would. A team of researchers from <keyword id="20239252" type="General" weightage="20" keywordseo="Google-DeepMind" source="keywords" meta.keywordsubtype="org" meta.entityname="Google DeepMind" meta.hostid="261" meta.entityid="Google DeepMind">Google DeepMind</keyword>, along with computer scientists and sociologists, has developed a groundbreaking AI system capable of creating eerily accurate simulations of individual personalities, blurring the line between technology and identity. This innovative system uses artificial intelligence to analyse responses in real-time, generating what the researchers call “personality agents.” While the concept might conjure up images of clones or digital twins, the team is quick to point out that their aim is far less dystopian. Instead, they see it as a tool to revolutionise sociology and research, making it faster, cheaper, and more precise to study how people think and feel about the world around them. The process begins with a two-hour interview conducted by a conversational AI through an interface designed to be intuitive and engaging. A friendly 2D sprite represents the AI interviewer, its white circle pulsating as it speaks. When it’s the participant’s turn, the sprite morphs into a microphone icon, capturing their responses while a progress bar keeps track of the session. It’s an almost game-like experience, but beneath the surface, the AI is hard at work. By analysing speech patterns, preferences, and decision-making tendencies, it constructs a digital personality — a model capable of answering questions with an impressive 85% accuracy compared to the real person, as claimed by the researchers. The researchers, who interviewed 1,000 participants to train the system, are confident in its potential. They envision it as a game-changer for sociology, a field that relies heavily on surveys to understand human behaviour. Traditional surveys are time-consuming and expensive, requiring researchers to draft, distribute, and analyse them meticulously. With AI-generated <keyword id="24219225" type="General" weightage="20" keywordseo="personality-agents" source="keywords">personality agents</keyword>, researchers could simulate responses to different scenarios without needing to interview thousands of individuals each time. This could dramatically reduce costs while increasing the scale and precision of social research. The implications, however, extend beyond academia. The ability to simulate personalities could transform personal AI assistants, making them more intuitive and personalised. Imagine a digital assistant that truly “gets” you, anticipating your needs and preferences with uncanny accuracy. The technology could also enhance <keyword id="24219229" type="General" weightage="20" keywordseo="human-robot-interaction" source="keywords">human-robot interaction</keyword>, paving the way for robots that respond to emotions and situations as naturally as humans. Of course, the concept isn’t without its challenges. The ethical considerations are significant — how do we ensure consent when creating and using these digital replicas? What happens if someone uses this technology maliciously? For instance, these AI models could be weaponised in targeted advertising or political campaigns, using their deep understanding of a person’s preferences to subtly manipulate behaviour. There’s also the psychological discomfort of knowing your digital "self" could be interacting with others in ways you can’t control, potentially leading to trust issues or even emotional harm. The researchers acknowledge these concerns but emphasise their focus on transparency and ethical development. For now, they’re prioritising its use in <keyword id="24219226" type="General" weightage="20" keywordseo="sociological-research" source="keywords">sociological research</keyword>, but the possibilities for broader applications are undeniable. Whether that future excites or unsettles you, one thing is clear: the line between human and machine is becoming increasingly blurred. The findings of this research have been published in a preprint journal and can be accessed <a href="https://dx.doi.org/10.48550/arxiv.2411.10109">here</a>.

Researchers have created an AI that can simulate your personality with 85% accuracy after a 2-hour chat!

Here’s a fun twist you might not expect: a recent study shows that most people can't tell if a poem was crafted by a human or AI — and even more surprising, we often prefer the AI versions! Researchers Brian Porter and Edouard Machery from the University of Pittsburgh put this theory to the test, and the results reveal something pretty quirky about our poetic tastes. <h2>Human or AI? You decide!</h2>For this experiment, Porter and Machery recruited over 1,600 participants and gave them a batch of <keyword id="6355263" type="General" weightage="20" keywordseo="poetry" source="Orion">poetry</keyword> to read. Each participant got ten poems, five written by legendary poets like William Shakespeare, Emily Dickinson, Lord Byron, and T.S. Eliot, and five crafted by ChatGPT-3.5 mimicking these poets’ styles. Participants had no idea which ones were real and which were AI. <div type="Article" hostid="261" msid="115273975" title="5 interesting takeaways from Slack&amp;#39;s survey of 17,000 desk workers about AI" mstype="2" mssubtype="0"></div>The shocker was that readers were more likely to think the AI poems were written by humans! In fact, the poems people thought least likely to be human were often written by the very poets we’d consider masters of the craft. <h2>What makes a poem feel "real"?</h2>Curious to dive deeper, the researchers set up a second experiment with 696 new participants. This time, each reader rated poems on things like beauty, emotion, rhythm, and originality. The readers were divided into three groups: some were told the poems were written by humans, others by AI, and a third group got no information at all. <div type="Article" hostid="261" msid="115299674" title="Instead of killing jobs, there&amp;#39;s a strange AI hiring boom happening, according to Marc Andreessen" mstype="2" mssubtype="0"></div>They found that if you tell someone a poem was AI-generated, they’re likely to rate it lower on just about every quality. But here’s the twist: when people didn’t know who wrote the poems, they often rated the AI-generated ones higher than the human written ones! <h2>So, why are we falling for AI poetry?</h2>Turns out, AI poems often end up being a little more straightforward and easy to enjoy, while poems by famous poets can be more complex and challenging. Instead of appreciating the depth of a classic poet’s work, readers sometimes mistake complexity for confusion and move on. <keyword id="23985627" type="General" weightage="20" keywordseo="AI-generated-poems" source="keywords">AI-generated poems</keyword>, meanwhile, serve up their message in a style that feels familiar and easy to “get,” making them more enjoyable at first glance. Basically, we tend to believe we’ll prefer human poetry. But in reality, AI’s smooth style is just easier to like — and we interpret this as a sign the poem was created by a human. The findings of this research have been published in Scientific Reports and can be accessed <a href="https://dx.doi.org/10.1038/s41598-024-76900-1">here</a>.

New study finds readers can’t tell AI poems from human ones — and they often prefer AI

Will AI take over humanity? Will it be a threat in the near future? Or Will it be a blessing in disguise and make our lives easier? These are some questions that are being asked today as the world adapts to the “AI way of life.” Ever since OpenAI launched its generative AI chatbot, ChatGPT, discussions around AI’s impact on humanity have been surfacing. While a set of people believe that AI will eventually take over humanity, others are more optimistic about its impact. Not just the people, even the “Godfathers of AI”, whose work made the likes of ChatGPT possible, have different views over its impact. <keyword id="20943380" type="General" weightage="100" keywordseo="geoffrey-hinton" source="keywords">Geoffrey Hinton</keyword>, <keyword id="21043756" type="General" weightage="20" keywordseo="yoshua-bengio" source="keywords">Yoshua Bengio</keyword>, and <keyword id="20082643" type="General" weightage="20" keywordseo="yann-lecun" source="keywords">Yann LeCun</keyword> together received the 2018 Turing Award for their impressive work in deep learning and got the title of “Godfathers of AI.” While they all played pivotal roles in creating the foundations of AI, their views on its future diverge sharply. <h2>Geoffrey <keyword id="23515511" type="General" weightage="20" keywordseo="hinton" source="keywords">Hinton</keyword> is afraid of his own creation</h2> Hinton recently made headlines for winning a Nobel Prize in Physics along with Professor John Hopfield for their work in machine learning. However, after winning the award, he had a warning for all. “Quite a few good researchers believe that sometime in the next 20 years, AI will become more intelligent than us, and we need to think hard about what happens then,” he said as per a report in Independent.co.uk. “If you look around, there are very few examples of more intelligent things being controlled by less intelligent things, which makes you wonder whether when AI gets smarter than us, it’s going to take over control,” he added. This wasn’t the first time that Hinton warned the world about his own creation. Last year, he left his job at Google to speak out about his growing concerns over AI’s trajectory. In an interview with MIT Technology Review, Hinton had explained his departure from Google as motivated by his desire to speak openly about these dangers: “I want to talk about AI safety issues without having to worry about how it interacts with Google’s business” . Since then, he has been candid about his anxieties surrounding the potential consequences of AI. During the same MIT Technology Review interview, he had also said referring to AI and people’s obsession with it, “Sometimes I think it’s as if aliens had landed, and people haven’t realised because they speak very good English.” In various other interviews, Hinton has time and again painted an increasingly alarming picture of AI’s rapid evolution. He believes that as these systems continue to develop, they may ultimately achieve a form of intelligence superior to human cognition. Hinton has also voiced concerns that we are on a path towards a reality where AI outpaces human control. While there have been ample discussions about the potential of people losing their jobs due to AI, for Hinton, AI poses threats that go much beyond that. He worries about the existential risk it might present. In an interview with CBS News’ 60 Minutes, Hinton had said that AI will be able to manipulate people in future as the technology has learnt from all the books that were ever written. "They will be able to manipulate people, right?" he had said and added, "And these will be very good at convincing people because they'll have learned from all the novels that were ever written — all the books by Machiavelli, all the political connivances, they'll know all that stuff. They'll know how to do it." At the same time, he has also said that the AI threat might not materialise at all. In response to an inquiry from Business Insider’s Jordan Hart, Hinton had said that it could be anywhere from five to 20 years before AI might pose a real risk. He also acknowledged the possibility that such a threat may never come to pass, depending on how advancements in AI are managed. Hinton has also drawn comparisons between AI’s threat and that of nuclear weapons, underscoring his conviction that a concerted, international regulatory approach might be essential for curbing AI’s potential dangers. In an interview with Reuters last year, Hinton described AI as a potential risk even more pressing than climate change. While he underscored the importance of addressing climate issues, he argued that AI’s potential hazards might demand faster action. He noted that climate change solutions are relatively well understood—cutting carbon emissions can gradually mitigate the problem. However, with AI, the path forward remains unclear, leaving scientists and policymakers without a straightforward solution. <h2><keyword id="19911549" type="General" weightage="20" keywordseo="meta" source="keywords">Meta</keyword>’s top AI scientist is in favour of AI </h2> Yann <keyword id="21026889" type="General" weightage="20" keywordseo="lecun" source="keywords">LeCun</keyword> was also the recipient of the Turing award along with Hinton. Now working as Meta’s chief AI scientist, LeCun once used to be a student of Hinton. However, his views on AI’s impact are in stark contrast to that of his former teacher. LeCun has remained an outspoken advocate for AI, dismissing warnings of AI-induced existential threats and asserting that fears of AI surpassing humanity are “ridiculous.” LeCun, who joined Meta in 2013 as the founding director of its AI research lab, has been quick to dismiss the notion that AI will outpace human control or evolve into a “rogue intelligence.” He has argued that these fears stem more from human imagination than from technical reality. “If it were the case, we would have AI systems that could teach themselves to drive a car in 20 hours of practice, like any 17-year-old,” LeCun quipped in an X post in response to Elon Musk’s fears about AI surpassing human intelligence . LeCun’s optimistic outlook is shaped by his belief that current AI systems, including large language models like ChatGPT and Meta’s own Llama 2, are still far from developing a genuine form of understanding. According to LeCun, fears of a “hard take-off”—where AI suddenly achieves runaway intelligence—are misguided. In an interview with Wired last year, he said that fear around AI was being “exploited” and that every revolutionary technology is scary at first. He had said, “AI will bring a lot of benefits to the world. But people are exploiting the fear about the technology, and we’re running the risk of scaring people away from it. That's a mistake we made with other technologies that revolutionized the world. Take the invention of the printing press in the 15th century. The Catholic Church hated it, right? People were going to be able to read the Bible themselves and not talk to the priest. Pretty much all the establishment was against the wide use of the printing press because it would change the power structure. They were right—it created 200 years of religious conflict. But it also brought about the Enlightenment.” Moreover, speaking at a Meta event in Paris, LeCun termed fears around AI as “preposterously ridiculous” and said that AI is a promising tool, not an existential risk. According to him, while AI may eventually surpass human intelligence, this is likely decades away. He told BBC that it would be a “huge mistake” to restrict AI research, arguing that concerns stem from a lack of understanding on how to make AI safer. While LeCun dismisses the notion of AI becoming uncontrollably intelligent, he does support the development of open-source AI, which he believes could democratize the technology and mitigate risks associated with centralized control. In a letter to President Joe Biden, LeCun and other AI scientists advocated for an open-source approach, contending that AI should not be monopolized by a select few companies. <h2>The future of AI </h2> Thus, the two Godfathers of AI have opposite views on AI and their views echo larger tensions in the tech industry. The rapid advancement of generative AI tools has rekindled discussions over whether governments should intervene to regulate AI’s development. The US, the EU, and other countries have proposed frameworks aimed at governing AI, with some leaders calling for bans on AI in military applications or strict controls on its use in sensitive sectors. While Hinton is a strong advocate for such restrictions, LeCun cautions against excessive regulation, arguing that too many constraints could stifle innovation. In an interview with BBC, LeCun had said that “keeping AI research under lock and key” would be a mistake. . The disagreement also extends to how AI’s impact on employment and societal roles is perceived. While Hinton warns of mass job displacement as machines take over increasingly complex tasks, LeCun remains unperturbed by such projections. He often argues that AI will complement rather than replace human work, citing past technological revolutions, like the industrial and digital ages, as examples of how new technology can create more opportunities than it displaces.

Threat or not? The Godfathers of AI spar on their views about its impact

A recent study from the <keyword id="23681499" type="General" weightage="20" keywordseo="Ludwig-Maximilian-University" source="keywords">Ludwig Maximilian University</keyword> of Munich has shed light on a growing concern in the world of <keyword id="20016198" type="General" weightage="20" keywordseo="journalism" source="keywords">journalism</keyword>: the comprehensibility of <keyword id="23681497" type="General" weightage="100" keywordseo="AI-generated-news" source="keywords">AI-generated news</keyword> articles. Despite advancements in artificial intelligence, the study found that readers still prefer traditionally crafted news pieces. The study surveyed over 3,000 UK-based online news readers, each evaluating one of 24 <keyword id="23681500" type="General" weightage="20" keywordseo="news-articles" source="keywords">news articles</keyword> — half written by humans and half produced by automation. The findings? Despite editorial oversight from journalists, AI-generated articles fell short on comprehensibility compared to their human-authored counterparts. Lead author Sina Thäsler-Kordonouri noted that readers found automated articles “significantly less comprehensible” overall. One key complaint revolved around language choice in AI articles, with readers pointing out an excess of unusual or overly complex words. Another significant sticking point was how AI-handled numbers and data. For many readers, this treatment was confusing and disrupted the flow of the article, leaving them less satisfied with the <keyword id="23681501" type="General" weightage="20" keywordseo="automated-content" source="keywords">automated content</keyword>. <div type="Article" hostid="261" msid="114568958" title="ChatGPT parent OpenAI is reportedly planning to launch a new AI model soon but not everyone will get it" mstype="2" mssubtype="0"></div>Interestingly, readers did find parity between the two types of articles in terms of narrative flow and structure. However, the challenging word choice and awkward handling of data remained a stumbling block for AI-produced articles. Professor Neil Thurman, who headed the project, emphasised that refining the automated content process could help bridge the <keyword id="23068619" type="General" weightage="20" keywordseo="readability" source="keywords">readability</keyword> gap. This includes not only simplifying language but also finding ways to make data-driven content more intuitively understood by readers. This research highlights the nuanced role of human editors in AI content creation. As newsrooms consider AI’s potential, balancing efficiency with clarity remains key. “Our results indicate the importance not only of maintaining human involvement in the automated production of <keyword id="23681502" type="General" weightage="20" keywordseo="data-driven-news" source="keywords">data-driven news</keyword> content but of refining it,” said Thäsler-Kordonouri. While automation is here to stay, this study makes one thing clear: a human touch still plays a critical role in making news accessible and engaging. <div type="Article" hostid="261" msid="114424676" title="Meta AI will be able to remember your WhatsApp chat with a new feature, know all about it" mstype="2" mssubtype="0"></div>

Can AI really take over journalism? Study shows why readers still prefer human-written news articles over AI-crafted pieces

<ul class="summary-list"><li>Trump has nominated Robert F. Kennedy Jr to lead the Department of Health and Human Services.</li><li>The president-elect previously vowed to let Kennedy "go wild on health."</li></ul>Trump has nominated former presidential candidate Robert F. Kennedy Jr. to lead the Department of Health and Human Services, likely sparking a confirmation battle in the Senate."I am thrilled to announce Robert F. Kennedy Jr. as The United States Secretary of Health and Human Services (HHS)," Trump wrote on Truth Social. "For too long, Americans have been crushed by the industrial food complex and drug companies who have engaged in deception, misinformation, and disinformation when it comes to Public Health.The president-elect previously vowed to let Kennedy "go wild on health."Kennedy, 70, is a vaccine skeptic who supports removing fluoride from water supplies and promoting products like raw milk, which the Food and Drug Administration has cautioned against. He has said that he wants to fire some nutritionists at the health agency and overhaul federal food regulations, setting off alarm bells among public health experts. Yet his eclectic views occasionally cut across party lines — his desire to cut ultra-processed food from school lunches, for example, was an Obama-era priority as well.Despite once running against Trump this cycle, Kennedy dropped out and <a target="_blank" href="https://www.businessinsider.com/rfk-jr-drops-out-presidential-race-2024-8">endorsed</a> the president-elect in August, which <a target="_blank" href="https://www.businessinsider.com/rfk-wanted-white-house-job-exchange-for-endorsing-trump-report-2024-7">sources</a> said was an effort to secure a job in the administration. The two spearheaded a "Make America Healthy Again" campaign.The head of HHS requires Senate approval and Kennedy could have an upward battle ahead of him, <a target="_blank" href="https://www.semafor.com/article/11/12/2024/trump-eyes-a-battle-to-get-kennedy-through-the-senate">Semafor reported</a>.

Trump taps Robert F. Kennedy Jr. to lead Department of Health and Human Services

With how easy they can make our day-to-day lives, it is easy to get swept up by the impressive achievements of apps like <keyword id="19918826" type="General" weightage="20" keywordseo="ChatGPT" source="keywords">ChatGPT</keyword>, Midjourney, and <keyword id="20055508" type="General" weightage="20" keywordseo="DALL-E" source="keywords">DALL-E</keyword>. These <keyword id="21195046" type="General" weightage="20" keywordseo="AI-applications" source="keywords">AI applications</keyword>, powered by <keyword id="19897804" type="General" weightage="20" keywordseo="large-language-models" source="keywords">large language models</keyword> (LLMs), can generate text, create images, and hold conversations that mimic human interactions. But according to a recent study by Apple Computer Company researchers, the intelligence displayed by these AI systems is far from genuine. <h2>The illusion of intelligence</h2>The Apple research team, led by a trio of AI experts, conducted a series of tests on various popular LLMs. They found that while these models appear intelligent on the surface, their responses are often unreliable when asked to perform tasks requiring true <keyword id="21233087" type="General" weightage="20" keywordseo="logical-reasoning" source="keywords">logical reasoning</keyword>. This discrepancy, they argue, reveals that LLMs don’t actually “understand” the questions they’re answering. Instead, they simply recognise familiar patterns and respond based on statistical probabilities, rather than meaningful comprehension. To illustrate this point, the researchers used a simple analogy: imagine a child asking their parent how many apples are in a bag. The child also mentions that some of the apples are too small to eat. Both the child and the parent understand that the size of the apples has no bearing on their quantity. However, when <keyword id="19924380" type="General" weightage="20" keywordseo="AI-models" source="keywords">AI models</keyword> are presented with similarly structured questions — questions with information that can be considered unnecessary (like the size of the apples) — they frequently become confused, offering nonsensical or incorrect answers. <div type="Article" hostid="261" msid="114046455" title="Love ChatGPT and Alexa? This year’s Physics Nobel Prize has been awarded to two scientists who made these AI technologies possible" mstype="2" mssubtype="0"></div>In their study, the researchers asked the AI models hundreds of questions, including some with non-pertinent details. They found that even minor changes in phrasing or context were enough to throw off the models. These AIs, despite their advanced programming, struggled to filter out irrelevant information, suggesting that they lack the capacity for genuine logical reasoning. <h2>How do modern AI apps work?</h2>Understanding why AI models like ChatGPT struggle with logic and nuance requires a closer look at how these systems function. At their core, LLMs are based on complex machine learning algorithms that analyse vast amounts of text data to learn language patterns. Once trained, these models use probabilities to generate responses based on what they’ve seen in their training data. However, they don’t “understand” language the way humans do. When an LLM receives a prompt, it breaks down the text into tokens and predicts the next word in a sequence based on statistical likelihood. This approach allows the AI to generate coherent, contextually relevant responses but doesn’t equip it to handle questions that require deeper, contextual reasoning. In essence, AI models are mimicking language without truly grasping the meaning behind it. To elaborate on the earlier example, if asked, “How many apples are in a bag if three are too small to eat?” a human would immediately recognise that the size of the apples has no impact on the total count. An AI, on the other hand, may get tripped up by the additional detail and offer a convoluted response because it cannot separate what’s important from what’s not. Apple’s researchers suggest that this limitation is a fundamental flaw in how AI models are designed. While the technology has advanced rapidly, the underlying mechanics remain rooted in <keyword id="20034261" type="General" weightage="20" keywordseo="pattern-recognition" source="keywords">pattern recognition</keyword> rather than true comprehension. As a result, today’s AI applications are better suited for tasks that involve straightforward pattern matching, like language translation or text prediction, but struggle when asked to exhibit <keyword id="23580940" type="General" weightage="20" keywordseo="human-like-intelligence" source="keywords">human-like intelligence</keyword>. <h2>Overestimating AI capabilities can have risks</h2>Because these modern AI models can produce remarkably human-like text, many have a tendency to attribute greater intelligence and understanding to them than they actually possess. This misconception can lead to unintended consequences, such as relying on AI for critical decision-making in areas where accuracy and logical reasoning are paramount — such as in business decisions as more and more companies adopt AI. <div type="Article" hostid="261" msid="114284609" title="Even high school interns are able to use common AI tools to bypass security and launch bots on X, Facebook and other social media: report" mstype="2" mssubtype="0"></div>The researchers also caution that the “illusion” of intelligence can make it difficult for users to recognise when an AI is providing incorrect information. In their tests, Apple’s team noted that LLMs frequently gave answers that sounded correct on the surface but fell apart upon closer inspection. These findings highlight the importance of scrutinising AI-generated content and using these tools as supplements to human expertise rather than replacements for it. As AI continues to evolve, researchers will need to explore new approaches that go beyond pattern recognition. Achieving genuine AI intelligence will likely require breakthroughs in fields like cognitive computing and neuromorphic engineering — fields that aim to create systems capable of human-like understanding and reasoning. For now, the takeaway from Apple’s research is clear: despite their impressive capabilities, today’s AI apps are tools, not thinkers. As Apple researchers pointed out, these models are designed to simulate understanding but lack the cognitive depth to handle complex reasoning. Recognising these limitations is crucial as we integrate AI into more aspects of our lives. The findings of this research have been published in a preprint server and can be accessed <a href="https://dx.doi.org/10.48550/arxiv.2410.05229">here</a>.

Apple engineers assert the AI apps of today are essentially still just fakes that lack 'true' intelligence

<ul class="summary-list"><li>Tesla's robots serving drinks and talking to guests at the "We Robot" were partly controlled by humans.</li><li>The robots' performance quickly raised skepticism about their true capabilities and independence.</li></ul>Tesla's robots might have wowed viewers at its <a target="_blank" class="" href="https://www.businessinsider.com/tesla-robotaxi-event-cybercab-elon-musk-2024-10">"We Robot" event</a> Thursday by serving drinks, answering questions, and playing rock-paper-scissors, but people were quick to suspect that the performance was too good to be true.It turns out they were right.Tesla CEO Elon Musk proudly showed off the latest version of his Optimus robots, which were last seen in September <a target="_blank" class="" href="https://www.businessinsider.com/tesla-robot-optimus-yoga-video-2023-9">sorting blocks and doing yoga poses,</a> during the event. Musk, who said Tesla had been making progress on the humanoid robots, predicted they would become "the biggest product ever of any kind."The robots walked into the spotlight closely flanked by Tesla engineers."One of the things we wanted to show tonight is that Optimus is not a canned video, it's not walled off," Musk said. "The Optimus robots will walk among you. Please be nice to the Optimus robots. So you'll be able to walk right up to them and they'll serve drinks at the bar."<div type="image" title="Tesla Optimus robot" height="1112" width="1482" msid="114227285" hostid="261" sizebytes="43984"></div>Morgan Stanley analysts wrote in a note on Friday that the robots weren't fully operating independently and "relied on tele-ops," or humans controlling them behind the scenes."Overall, we did not pick up on anything new/novel about Optimus that clearly showed significant progress," the analysts wrote. "Including little incremental detail from the company that the market was not previously aware of. "Videos of guests' interactions with the Optimus robots posted online underscored that humans were involved.One attendee <a target="_blank" class="" href="https://x.com/zhen9436/status/1844773471240294651">posted a video</a> on X, formerly Twitter, asking an Optimus robot operating a beer tap if it was remote-controlled, to which it responded that it was "assisted by a human." "I'm not yet fully autonomous," the voice said, with a human-sounding trip over the word "autonomous."Another <a target="_blank" class="" href="https://x.com/Scobleizer/status/1844594008225611858">video</a> showed a guest trying to get the robot to reveal how much of it was actually AI and not a human. "I can't disclose just how much, that's something you'll have to find out later," the voice said. "I would say, it might be some. I'm not going to confirm, but it might be some."Although some commenters felt the human assistance was "obvious," others said that Tesla's presentation was misleading.Tesla influencer Jeremy Judkins <a target="_blank" class="" href="https://x.com/jeremyjudkins_/status/1845157754778050895?s=61&amp;t=GzPrMPqx1H24t4TRy2DnQQ">wrote on X</a> that he didn't realize the bots were human-controlled until after the event, saying Tesla "misled millions of people" who watched the livestream.Josh Wolfe, cofounder of Lux Capital, also seemed to disapprove."Totally worthy to celebrate low latency remote control but totally dishonest to demo these as autonomous robots—call it the parlor trick it is," he <a target="_blank" class="" href="https://x.com/wolfejosh/status/1844713270747259391?s=61&amp;t=GzPrMPqx1H24t4TRy2DnQQ">wrote</a>.Tesla did not immediately respond to Business Insider's request for comment.Musk said he envisions a future where "Optimus robots will walk among you." The Tesla CEO expects it to become a household companion, likening it to a personal "Star Wars" R2-D2 or C3-PO that can pick up your groceries and babysit your kids.Musk, who has said he is "pathologically optimistic," has also said that Optimus will boost Tesla's valuation into the trillions.Tesla has said it's <a target="_blank" class="" href="https://www.businessinsider.com/tesla-says-two-optimus-humanoid-robots-working-in-factory-autonomously-2024-6">already deployed two</a> Optimus robots on its factory floor, though it is unclear what tasks they are completing. Tesla has said the humanoid robots will eventually be sold to both companies and consumers.Musk predicted an eventual price tag of $20,000 to $30,000 price tag — "probably less than a car"— when manufactured at scale, which he said would take some time.Do you work at Tesla and have a story to share? Reach out to the reporter from a non-work email and device at aaltchek@businessinsider.com

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Researchers have created an AI that can simulate your personality with 85% accuracy after a 2-hour chat!

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