How To Gain Vital Skills In Conversational Icebreakers Via Nimble Use Of Generative AI
Josh Hawkins has been writing for over a decade, covering science, gaming, and tech culture. He also is a top-rated product reviewer with experience in extensively researched product comparisons, headphones, and gaming devices. The latest catchphrase to refer to AI which has been mindfully calibrated and prepared to cope with the physical world is referred to as Physical AI.
It is all happening without any particular controls or stipulated regulations, see my analysis of what we need to do about this at the link here. The AI came out quickly with several useful suggestions that are all reasonable and not somehow odd or outlandish. Another aspect to note is that the AI didn’t ridicule me or otherwise play any tomfoolery about my need for assistance. Generative AI is typically shaped to be supportive rather than combative.
For example, you might invoke an agentic AI that would book your hotel rooms and flights for a vacation trip. I know that smarmy types will exhort that everyone knows that to be the case, but I dare suggest that it isn’t as widely understood as the cheeky cynics might declare. People are often unsure of what led to generative AI being able to respond. There is a tad bit of mystery at times and users just assume something magical is taking place. Aha, the AI is doing its calculations and responses based on data and not on any real-world first-hand experience. I’m assuming that if I asked you the same question, your answer would be about the same.
The AI told the truth, namely that it was speculation based on text-based pattern-matching of content that ChatGPT had been initially data trained on. A heated debate in the AI community entails whether we truly need to have AI essentially “embody” physicality considerations such as my point earlier of generative AI by words versus generative AI by deeds. With a grain of salt, analogize this to the human mind that is without a body. Maybe the AI must have a “body” or at least a semblance of embodiment to fully grasp how to operate in the physical world. You can have Physical AI that is not beholden to either of those other two types of AI. It is simply Physical AI and doesn’t have generative AI or agentic AI involved.
Adding OT data brings these models to life, accurately simulating complex scenarios in near real time. These use cases deliver impressive ROI — at least on paper and in the lab. However, physical AI technology the likes of Nvidia Cosmos is new, and interfacing with OT equipment is often problematic for all the reasons touched on above, so the timeline is still uncertain. Nvidia’s “right around the corner” time estimate for physical AI is vague because two technical barriers prevent Huang (and me) from providing a specific timetable. First, physical AI requires new, real-world, physics-aware models and unique development platforms. Second, despite compelling business cases and a decade of IoT development, most data produced by OT is still inaccessible to IT systems and AI-powered business applications.
Cosmos then uses generative AI to populate Omniverse scenes, leveraging its WFMs to generate photorealistic, geospatially accurate scenarios. Cosmos then synthesizes additional scenarios to create a multiverse of training data with many combinations of diverse and unexpected situations. Omniverse simulates these scenes, capturing visual data from various points of view, which enables developers to train, validate, test and optimize the target model. Our community is about connecting people through open and thoughtful conversations. We want our readers to share their views and exchange ideas and facts in a safe space.
Soko Glam skin care uses Ada’s chatbot to provide personalized product recommendations around the clock. The opening, as usual, developed with both bots displaying precision. Stockfish confidently maneuvered into a textbook Sicilian, while ChatGPT initiated an aggressive pawn storm on the kingside. But when things got complicated in the middle of the game, ChatGPT started playing moves so bewilderingly they bordered on art.
Although AI creates extremely compelling integration business cases, most operational data remains isolated from large-scale AI because of the complexity, cost, and security risks of connecting OT systems with mainstream IT. This is the OT-IT gap — the chasm between the heterogeneous, chaotic world of industrial IoT and the uniform, managed world of IT. The game started innocently enough, with both bots making standard moves. Stockfish, ever the perfectionist, methodically built its position, while Snapchat AI seemed to have a decent grasp of opening chess fundamentals—until it didn’t. The match was most interesting for the light it shed on pure AI—that is, models trained at specific tasks based on predefined rules—versus generative AI, or models trained to generate new content based on previous information. We guide our loyal readers to some of the best products, latest trends, and most engaging stories with non-stop coverage, available across all major news platforms.
The somewhat new angle is that we will have generative AI working at the core of Physical AI, which then we might coin as Generative Physical AI. Reality and physical movement are like the air we breathe; it is all around us and we conventionally take it for granted. Later in life, during school and intense classes in physics and math, they will get a grand revealing of the explicitly calculated secrets underlying the physical world. Until then, it is mainly a sense of embodied presence in the real world, entailing physicality and nature’s intrinsic bodily dynamics, along with a spoonful of mindful geospatial mapping. Suppose that you have a friend or colleague who seems to be having trouble breaking the ice with other people, and you want to aid in overcoming the difficulty. You could use generative AI to gear up for providing such assistance.
It might seem that some people are naturally able to start conversations. Turns out that generative AI can be quite helpful in getting you into an icebreaker mindset and bolster your confidence for that next moment where you need to suavely begin a conversation. Wax & Wane Candles created professional branding using Canva’s AI. The Little Market integrated free Google AI tools into its inventory system, leveling the playing field with larger competitors.
Similarly, AGX is the native, optimized robotics platform target for Nvidia’s physical AI models. However, industrial customers need the flexibility to run AI applications across diverse physical AI embodiments. Platform targets vary from microcontroller-based sensors with modest ML inference acceleration to robotics computers capable of running large generative AI models, so AGX platforms aren’t always appropriate deployment targets. To put it another way, platform choice is use-case dependent, not a product selection decision like which GPU to buy. Cosmos works with Omniverse, Nvidia’s graphics collaboration platform, to create realistic simulations for training physical AI systems. Development begins by using Omniverse to build realistic 3-D models of real-world facilities, machinery, robots and other equipment.
As shown in the response by ChatGPT, the method of figuring out what would happen once the rubber ball was let go consists of using the data training that the AI underwent when first being set up. The AI maker of ChatGPT, OpenAI, had scanned the Internet widely and used the various data on the Internet to establish patterns of how people write and describe things. In there, certainly, there would be plenty of content about physics and how physical objects in the real world move and act.
Nvidia has optimized its AI development toolchain for DGX and OVX platforms, much like the company optimized its CUDA software for its GPUs. ChatGPT had promoted pawns that didn’t exist, declared checkmates that weren’t real and clung to its illegality like a badge of honor. And just as the game seemed destined for a one-sided Stockfish victory, ChatGPT pulled a rabbit—or rather, a queen—out of its hat. With an audacious counterattack, it illegally awarded itself a queen and threatened Stockfish with a checkmate.
I put the word “know” in quotes to emphasize that today’s AI is not sentient and doesn’t know things in the same manner that humans do. AI is essentially software running on computer hardware and generative AI is specifically all about pattern-matching computationally on human writing such as essays, poems, stories, and the like. Maybe intellect is inextricably tied to the facets of having a body.
In some ways, it feels safer, especially if you don’t trust OpenAI. But essentially, Anthropic is doing what every other AI company currently does. It’s racing to develop better AI and readying new features consumers will appreciate. Amid the rush to devise and field Physical AI, it is incumbent upon AI makers and AI developers to keep in mind those wise words about what can happen once AI is operating in the physical world. Hark back to my dialogue with ChatGPT about how the AI figured out that a rubber ball would drop to the ground and bounce.
When this happens, the website server typically becomes overwhelmed, resulting in it being shut down because of too much traffic. I will tie this back to my comments about the duality of mind and body. This is something I do cautiously since I don’t want to anthropomorphize AI. AI that operates in the physical realm has been around since the earliest days of the AI field.
Machines and robots are going to be built and shipped to work side-by-side with humans. Physical AI will be the make-or-break of whether those mechanizations are compatible with humans and operate properly in the real world or instead are endangering and harmful. In preparing for meeting with people, it can be a valuable payoff to come up beforehand with some ready-made icebreakers.
ChatGPT has a Thursday lie down.
Posted: Thu, 23 Jan 2025 15:16:00 GMT [source]
Meta AI decided its bishop had outlived its usefulness and casually removed it from the board. If the first last two games were marred by rule-bending and necromancy, this game—also between two generative AI tyros—devolved into even more madness when Meta introduced AI mind control to chess. Things escalated when Grok attacked Gemini’s pieces—without taking anything. Both sides began flailing like toddlers in a food fight, with pieces left hanging, moved to illegal squares, or ignored.
For my coverage of how generative AI such as ChatGPT, Claude, Llama, Gemini, and other major AI is increasingly being connected to robotic arms and akin robotic capacities, see the link here. This type of usage of generative AI and LLMs is essentially a form of therapy. I have repeatedly cautioned that society is in a grand loosey-goosey experiment about the use of AI for mental health advisement. No one can say for sure how this is going to affect the populace on a near-term and long-term basis.
LLMs such as ChatGPT and Llama do not model the physical world. Developing accurate physical AI models for equipment such as robots, autonomous vehicles and industrial systems requires collecting, filtering, tagging and curating enormous amounts of real-world training data. To speed up this labor-intensive process, Nvidia has developed Cosmos, which it announced at CES 2025.
For a moment, it seemed like we might witness a serious game. Gemini confidently strutted through mainline theory like a seasoned grandmaster while Grok kept up with respectable moves, setting the stage for a proper showdown. While Claude is behind ChatGPT in some features, it is ahead in other ways. Anthropic has already released an early AI agent, while OpenAI has yet to announce ChatGPT’s “Operator” agent. If you’re a fan of generative AI programs like ChatGPT, Gemini, Claude, and others, and you have half an hour to spare, you should watch The Wall Street Journal’s interview with Anthropic Chief Executive Officer Dario Amodei. It’ll give you a different perspective than what you might have heard from other players in the AI field about what’s coming soon from products like ChatGPT.
The primary goal of icebreakers is to establish a connection with whomever you happen to meet, spark interest, and set a comforting foundation for engaging in a dialogue. Appearing at ease when employing an icebreaker is paramount to the process. Ideally, you might want to bounce off a friend or confidant the icebreakers that you intend to use. This person or advisor could help in refining the icebreakers. They would also serve to reject ones that might seem wonderful to you but are going to be disastrous if used in actual practice. There is little doubt that there are good icebreakers and the otherwise to-be-avoided disagreeable icebreakers.
Amodei also said that Claude might get a better memory so it can remember more about past conversations. The CEO also noted that Anthropic is looking to secure more computing power, as demand for Claude has surged in the last few months. Amodei said that all models do some reasoning, so the term isn’t really appropriate. Hee explained that Anthropic is developing other ways to improve Claude’s ability to reason.
But, more likely, Physical AI will be based on top of or at least in conjunction with either or both of those other two types of AI. The generative AI uses ostensibly book learning to guess what will happen when a robot is instructed by the AI to lift a chair or hold aloft a dog. Is that good enough to cope with the myriad of aspects that can go wrong? Perhaps the AI will by text-basis logic assume that if the dog is dropped, it will bounce like a rubber ball.
Another key facet is to deliver the icebreaker as though it is entirely off-the-cuff. Using a prepared icebreaker as though it was canned will almost be as bad as using a lousy icebreaker altogether. Seattle Ballooning solved this challenge by deploying a Voiceflow AI chatbot, dramatically increasing its conversion rates.
Speaking of online search, Claude doesn’t support that yet, while OpenAI has already deployed a ChatGPT Search model. But Amodei said that web integration is coming very soon to Claude. BGR’s audience craves our industry-leading insights on the latest in tech and entertainment, as well as our authoritative and expansive reviews. If you’ve never experienced a DDoS (Distributed Denial of Service) attack, then you’re probably not sure what to make of it. At the most basic level, these cyberattacks result from a threat actor sending an insanely large number of requests to a specific website or URL.
The AI then will act that way, and you can try to guide the AI in figuring out how to be an icebreaker. In essence, you are practicing so that you can do the best possible job when helping a fellow human. For more about how to tell generative AI to carry out a pretense, known as an AI persona, see my coverage at the link here. That said, there are a lot of real AI chess bots besides Stockfish; an actual tournament featuring the most popular ones has been around for years. In what passed for its end game, Snapchat AI devolved into a full-on tantrum, insisting on making illegal moves repeatedly. When Levy had enough of such nonsense, the bot decided it was a good idea to commit suicide and move its king so a pawn could take it.
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