Perplexity AI Makes A Bid To Merge With TikTok U.S.
The new structure would allow for most of ByteDance’s existing investors to retain their equity stakes and would bring more video to Perplexity, according to a source familiar with the situation.
Perplexity AI officially made a play for TikTok on Saturday, submitting a bid to its parent company, ByteDance, to create a new merged entity combining Perplexity, TikTok U.S. and New Capital Partners, CNBC has learned.
The new structure would allow for most of ByteDance’s existing investors to retain their equity stakes and would bring more video to Perplexity, according to a source familiar with the situation, who asked to remain anonymous due to the confidential nature of the potential deal.
Perplexity AI, the artificial intelligence search engine startup competing with OpenAI and Google, started 2024 with a roughly $500 million valuation and ended the year with a valuation of about $9 billion, after attracting increasing investor interest amid the generative AI boom — as well as controversy over plagiarism accusations.
AI-assisted search has been viewed by investors as one of Google’s key risks, as it potentially changes the way consumers access information online. Last year, OpenAI, which started the generative AI craze in late 2022 with ChatGPT, introduced a search engine called SearchGPT. Google later launched “AI Overviews” in search, allowing users to see a quick summary of answers at the top of results.
Though any potential transaction between Perplexity AI and ByteDance would likely take months to complete — and TikTok has said the app will “go dark” in the U.S. on Sunday unless the Biden administration assures it won’t punish Apple, Google and other service providers for hosting it.
More on Perplexity’s big to acquire TikTok US on CNBC
Humanoid Robots In Homes By 2026: John Koetsier With Peter Diamandis
It feels like we're at a tipping point right now in humanoid robotics. Models are getting released faster and faster, more and more capable than ever. Robots are actually taking paying gigs in warehouses and factories, and there's accelerating innovation.
Author, engineer, doctor, investor, and entrepreneur Peter Diamandis just released a major report on the entire industry, and together we dive into what's happening and what's changing. One prediction he made: we'll have humanoid robots in the home, helping us with our work, by 2026 in beta.
We discuss recent advancements, like the shipment of new models by Agility Robotics and Figure, and the development of Tesla's Optimus. Peter Diamandis shares insights from his extensive report on the state of humanoid robotics, highlighting key players in both the United States and China.
We also talk about the implications of having humanoid robots integrated into various industries, the potential for radically reduced labor costs, and the impact on global economics. And we touch on the broader societal impact, evoking considerations for purpose and struggle in a highly automated future.
Bruce Burke Participating In Forbes Entrepreneur Of Impact Competition
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Anthropomorphizing AI: Consequences Of Mistaking Human-Like For Human Have Already Emerged
In our rush to understand and relate to AI, we have fallen into a seductive trap: Attributing human characteristics to these robust but fundamentally non-human systems. This anthropomorphizing of AI is not just a harmless quirk of human nature — it is becoming an increasingly dangerous tendency that might cloud our judgment in critical ways. Business leaders are comparing AI learning to human education to justify training practices to lawmakers crafting policies based on flawed human-AI analogies. This tendency to humanize AI might inappropriately shape crucial decisions across industries and regulatory frameworks.
Viewing AI through a human lens in business has led companies to overestimate AI capabilities or underestimate the need for human oversight, sometimes with costly consequences. The stakes are particularly high in copyright law, where anthropomorphic thinking has led to problematic comparisons between human learning and AI training.
The language trap
Listen to how we talk about AI: We say it “learns,” “thinks,” “understands” and even “creates.” These human terms feel natural, but they are misleading. When we say an AI model “learns,” it is not gaining understanding like a human student. Instead, it performs complex statistical analyses on vast amounts of data, adjusting weights and parameters in its neural networks based on mathematical principles. There is no comprehension, eureka moment, spark of creativity or actual understanding — just increasingly sophisticated pattern matching.
This linguistic sleight of hand is more than merely semantic. As noted in the paper, Generative AI’s Illusory Case for Fair Use: “The use of anthropomorphic language to describe the development and functioning of AI models is distorting because it suggests that once trained, the model operates independently of the content of the works on which it has trained.” This confusion has real consequences, mainly when it influences legal and policy decisions.
More on the consequences of anthropomorphizing AI on VentureBeat
How To Build A Simple AI Agent In 5 Minutes With NVIDIA NIM
Harness the power of AI agents for content creation and digital illustration using NVIDIA NIM—a set of easy-to-use microservices designed for secure, reliable deployment of high-performance AI models inferencing across clouds, data centers, and workstations.
Zenodia Charpy, senior deep learning data scientist and solution architect at NVIDIA, walks you through how to set up two AI agents—one for content generation and another for digital graphic design.
This process uses Llama 3.1 405B, alongside stable diffusion models and server-side microservices, integrating LangChain for orchestration, and Gradio for seamless user interaction.
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OpenAI’s Ex-CTO Raids Rivals For Top Team At Her Artificial Intelligence Startup
Mira Murati’s still unnamed AI startup’s goal remains a mystery, but she clearly has a plan—starting with gathering a pool of industry experts.
Former OpenAI Chief Technology Officer Mira Murati has made the first hires for her own secretive AI startup, tech news site Wired reports. The list includes one very notable name: Jonathan Lachman, who was until recently the special projects lead at—surprise—OpenAI. The fact that Lachman has joined the list of senior staff who’ve left the nine year-old startup in recent months is notable, and so is the fact that Murati’s moving so fast to build out her new enterprise. It didn’t take long—Murati only left OpenAI in September last year.
Upon her departure, Murati made a statement explaining she’d made the “difficult decision to leave” so that she could “create the time and space to do my own exploration.” In October it emerged that she was already seeking $100 million in funding for her AI company which would be focused on “proprietary models,” news site TechCrunch reported. Since then, little new information has emerged about Murati’s plans…until now.
Industry news site Dataconomy.com says that Lachman is one of around 10 researchers and engineers from rival AI companies, including OpenAI, controversial social media chatting app Character AI and Google’s DeepMind. Despite these high-profile hires, Murati’s startup remains unnamed and “lacks a definitive product direction,” according to sources who spoke to Dataconomy.
The fact that Murati has attracted so many experts in just a handful of months does tell us one thing. It suggests that she has secured enough funding and has a convincing enough plan to tempt talented workers away from positions in other, already successful AI firms.
More on Mira Murati’s first hires for her AI startup on Inc.
Accenture’s Tech Vision At CES 2025 | AI: A Declaration of Autonomy
Dive into Accenture’s Tech Vision 2025, where Karthik Narian, Accenture's Group Chief Executive of Technology and Chief Technology Officer, hosts a fireside chat, moderated by Emily Chang, and featuring insights by Kevin Lopes, Vice President of Sports Business Development & Innovation for ESPN, Justin Boitano, Vice President of Enterprise AI, NVIDIA and Lan Guan, Accenture Chief AI Officer, delving into the scaled adoption of AI and how AI can revolutionize businesses and customer experiences.
The fireside chat discusses the importance of building both emotional and cognitive trust in AI. Emotional trust focuses on ensuring AI systems are responsible and ethical, while cognitive trust ensures they are reliable and accurate. By fostering this trust, organizations can create a robust and effective AI ecosystem that drives higher quality outcomes and frees up time for creative and strategic work.
Join us as we explore what happens when AI acts autonomously at the center of enterprise technology, speaks on behalf of your brand, inhabits robotic bodies and collaborates on behalf of employees—and learn how to prepare your organization for this transformative journey.
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Reddit Comments Are 'Foundational' To Training AI Models, COO Says
Reddit’s Jen Wong said the company's content is "foundational" to training AI models.
Last year was a big one for Reddit. The company went public in February. Then it began investing heavily in AI for features like its translation tool and an AI-powered search tool. It also struck agreements with Google and OpenAI that allow the tech companies to train their AI models using Reddit comments and posts.
Reddit COO Jen Wong says those investments are paying off. "AI itself, more broadly, is incredibly important to everything we're doing," Wong told AdExchanger at the CES technology conference. Wong added that Reddit is now "foundational to the training" of large language models.
In February, Reddit signed a licensing deal with Google to train Google's AI using Reddit content for $60 million a year. Then, in May, Reddit signed another massive content data-sharing deal with ChatGPT-maker OpenAI to train its AI models.
Reddit CEO Steve Huffman said the company is in talks with "just about everybody" when asked if Reddit would consider working with Microsoft during The Wall Street Journal's Tech Live event in October.
Huffman said Reddit posts and comments contain a wealth of "colloquial words about pretty much every topic" that are constantly updated, making them valuable in teaching machines.
More on Reddit’s AI efforts on Business Insider
Omdia Session At CES: AI At The Edge | Revolutionizing Consumer Electronics
As AI reshapes the data center with GenAI, the next frontier is already emerging—AI at the edge. At CES, Omdia and industry experts from Canalys, Lenovo, Microsoft, Qualcomm, and Wards Intelligence debated how in-device AI could revolutionize consumer electronics by addressing challenges like power consumption, latency, and connectivity.
Thats all for today, however new advancements, investments, and partnerships are happening as you read this. AI is moving fast, subscribe today to stay informed.