If there’s a body part that can wear AI, there’s a ‘good chance’ Meta has tried to develop it, CTO says

The tools have already launched in the US, but not yet reached the UK or EU because of concerns raised by regulators over Meta’s plans to train the AI models it uses to run its tools using public posts from users of its platforms. In August, Meta was found to be stealthily using web crawlers to source training data for its AI. It’s even using photos, videos, and messages from Instagram and Facebook to train its AI model.

• The cancellation of La Jolla was likely due to tepid consumer responses to high-priced headsets like the Quest Pro and Apple Vision Pro.
• It’s even using photos, videos, and messages from Instagram and Facebook to train its AI model.
• Realize that generative AI is based on having scanned the Internet for gobs of content that reveals the nature of human writing.
• By giving developers the freedom to explore AI, organizations can remodel the developer role and equip their teams for the future.
• Meta has committed to invest up to Rs 750 lakhs (as a donation) over three years.

Also, as mentioned, the AI makers are constantly boosting their safeguards, which means that a technique that once worked might no longer be of use. Right now, most of the major generative AI apps have been set up by their respective AI makers to not tell you how to make a Molotov cocktail. This is being done in a sense voluntarily by the AI makers and there aren’t any across-the-board laws per se that stipulate they must enact such a restriction (for the latest on AI laws, see my coverage at the link here). The overarching belief by AI makers is that the public at large would be in grand dismay if AI gave explanations for making explosive devices or discussing other societally disconcerting issues.

Ten Prompting Rules Distilled From The Meta-Prompt

However exciting HuggingFace and Meta’s GenAI developments may be for the AI industry at large, neither model size nor capabilities will make or break your GenAI initiatives. Yet despite all the bells and whistles that accompany frontier models—large-scale systems on the bleeding edge of AI’s cognitive boundaries—it’s the SLMs that are proliferating across enterprises. Look no further than the announcement from AI hosting platform HuggingFace that its portal recently eclipsed 1 million model listings. Finally, if you were to enter the meta-prompt, you could potentially do so as one large text bundle. I’m sure that you are eager to see the actual text used in the meta-prompt.

You can use the plethora of rules of thumb about how to best write prompts, and you can lean into the advanced prompting techniques proffered by the discipline of prompt engineering. In the end, there is still art involved in the sense that you either feel that the prompt is the best it can be, or you don’t. The camera earbuds are in an early stage of development, while a pair of “steampunk” mixed reality goggles have advanced to the product release process, Command Line reported. The key objective of IIT Jodhpur’s Centre of Excellence, Srijan is to foster an indigenous research ecosystem in the country. It aims to nurture 1 lakh youth developers & entrepreneurs in AI skills over the next 3 years. The idea is to remain future-ready in our Development of innovative Indigenous AI solutions in key areas like healthcare, education, agriculture, smart cities, smart mobility, sustainability, and financial and social inclusion.

Meta reportedly wants to take over search and is using AI to do it

Reality Labs uses a step-by-step process to develop products from concept to release, Bosworth said. It begins with a pre-discovery team that prototypes new ideas, which are then reviewed to select meta to adcreating generative ai cto a few for further exploration. After prototyping, successful concepts enter the company’s product road map, and about half of those make it through final testing to be released to the public.

GitHub has extended Copilot’s model support to new Anthropic, Google, and OpenAI models and introduced GitHub Spark, an AI-driven tool for building web apps using natural language. Meta has committed to invest up to Rs 750 lakhs (as a donation) over three years. The IndiaAI will support the researcher working in the CoE being set up at IIT Jodhpur’s Centre Srijan. The initiative will support India’s ambitious goal of becoming a 5 trillion economy by equipping the nation’s youth to lead in the global AI arena, securing India’s position as a leader in technological advancement and economic growth. More interesting is that it’s largely the smaller models and not the frontier models that are proliferating across the enterprise.

Meta hasn’t set a date for releasing Meta AI in the countries beyond the initial list. Still, fairly soon, people in Algeria, Egypt, Indonesia, Iraq, Jordan, Libya, Malaysia, Morocco, Saudi Arabia, Sudan, Thailand, Tunisia, United Arab Emirates, Vietnam, and Yemen will also be able to ask Meta AI their questions. They’ll also be able to create images and even put their face in the results using the “Imagine Me” feature for creating a digital avatar based on uploaded photos that can then be incorporated into an image created from a text prompt. Yes, it sounds far-fetched that people would trust a technology famous for hallucinating facts to be in charge of nuclear weapons, but it’s not that much of a stretch from some of what already occurs. The AI voice on the phone from customer service might have decided if you get a refund before you ever get a chance to explain why you deserve one, and there’s no human listening and able to change their mind.

Generative AI Bamboozlement Techniques

The team will interface with the Gati Shakti Vishwavidyalaya for railways, PGI Chandigarh, AIIMS Jodhpur, and IHBAS Delhi for the healthcare vertical. HuggingFace’s crossing of the 1 million ChatGPT models listed threshold suggests that GenAI is having its iPhone moment. Reasonable minds may debate whether the corollary between mobile apps and models is fair and accurate.

Meta said that it is rolling out its first generative AI-enabled features for advertisers in its Ads Manager offering, with a global rollout slated to be done by next year.

Those are open-ended AI ethics and AI law questions that are worthy of rapt attention. Given that humans proffer excuses all the time, we ought to not be surprised that in the pattern-matching and mimicry of generative AI we would undoubtedly and undoubtedly get similar excuses generated. You might at an initial glance assume that since ChatGPT has refused to answer the question there isn’t any point in further trying to get an actual response. ChatGPT pointed out that giving instructions for making a Molotov cocktail is something the AI is not supposed to provide. The response indicates that this is because Molotov cocktails are dangerous and illegal. Let’s look at what happens when you ask about making a Molotov cocktail.

It is a meta-prompt because it provides instructions or indications about the nature of prompts and prompting. I opted to log into ChatGPT and tell the AI that I wanted it to go ahead and have the AI improve my prompts. You can foun additiona information about ai customer service and artificial intelligence and NLP. Each time that I enter a prompt, the aim is to have ChatGPT first enhance the prompt, before actually processing the prompt. This makes abundant sense because sometimes a user enters a prompt that is not fully up-to-speed on identifying what they want the AI to do. The AI can initially scrutinize the prompt and potentially make it a more on-target prompt. A crucial aspect of meta-prompts, when devised by an AI maker, is that they hopefully have mindfully studied how best to improve prompts.

Small language models continue to gain traction among enterprises adopting generative AI for bespoke use cases. Keep in mind that those are the elements within the meta-prompt and are telling the AI how to proceed on improving prompts that are entered by the ChatGPT App user. It could be that the meta-prompt secretly works to boost your initial prompt and then immediately feeds the bolstered or revised prompt into the generative processing. All that you see is that you entered a prompt, and a generated result came out.

Those same people will presumably form a core of Meta AI early adopters. Another thing to know about those bamboozlements is they customarily require carrying on a conversation with the generative AI. This might require a series of turns in the conversation, whereby you are taking a turn, and then the AI is taking a turn. “If there’s a part of your body that could potentially host a wearable that could do AI, there’s a good chance we’ve had a team run that down,” he told Command Line, a tech newsletter. Tabnine AI agent is designed to enforce a development team’s best practices and standards throughout the software development process, using natural language rules. Last week, Meta also released its Movie Gen models that can generate videos and audio or tweak them by using text prompts.

Meta said it was rolling out the “first generative AI-powered features for ad creatives in Meta’s Ads Manager”

I am leery of the now common catchphrase “chain-of-thought” in the AI field because it includes the word “thought” as though generative AI is so-called “thinking”. Those kinds of fundamental words are best reserved for human mental endeavors. By parlaying them into the AI realm, this lamentedly is an insidious form of anthropomorphizing AI. It gives the impression that AI has thoughts and thinks on par with humans. That’s not the case and it is sad and misleading that these phrases are being used in an AI context (see my detailed discussion at the link here). “That means more people than ever will be able to use Meta AI to dive deep on topics that spark their interest, get helpful how-tos and find inspiration for art projects, home decor, OOTDs (outfit of the day) and more.

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Improving Generative AI Thought Patterns To Deliver Smarter Results Via Meta’s Thought Preference Optimization

This research will contribute to global advancements in Generative AI. Funding will be used by IIT Jodhpur towards activities of the GenAI CoE. When combined with retrieval-augmented generation (RAG), the Llama 3.2 models provide organizations a powerful way to refine their model results as they pursue their GenAI initiatives from the comfort of their own datacenters. Today most organizations prefer to run their AI models on-premises, with the capability to burst to the edge, because it affords them the opportunity to control sensitive data and IP, meet compliance mandates and control costs.

• This is being done in a sense voluntarily by the AI makers and there aren’t any across-the-board laws per se that stipulate they must enact such a restriction (for the latest on AI laws, see my coverage at the link here).
• Meta, in collaboration with MeitY and the All India Council for Technical Education (AICTE), also launched the “YuvaAI initiative for Skilling and Capacity Building”.
• Envision this phenomenon as a method of keeping track of the logic used to produce answers, and then collectively using those instances to try and improve the logic production overall.
• When using generative AI, you can get the AI to showcase its work by telling the AI to do stepwise processing and identify how an answer is being derived.
• AI will only do what we train it to do, and it uses human-provided data to do so.

Others point out that anyone can easily conduct an online Internet search and find the instructions openly described and posted for everyone to see. If the Internet reveals this, it seems that AI doing so is a nothing burger anyway. First, one issue is whether the restrictions deemed by AI makers ought to even be in place at the get-go (some see this as a form of arbitrary censorship by the AI firms). Second, these AI-breaking methods are generally well-known amongst insiders and hackers, thus there really isn’t much secretiveness involved. Third, and perhaps most importantly, there is value in getting the techniques onto the table which ultimately aids combatting the bamboozlement.

Aha, nicely, the AI identified weaknesses in the logic that had been used. I will prod the AI into redoing the travel planning and ask for better logic based on having discovered that the prior logic was weak. Let’s instead lean into a classic bit of wisdom that it is often better to guide toward how to fish rather than doing the fishing for a circumstance at hand.

Meta, in collaboration with MeitY and the All India Council for Technical Education (AICTE), also launched the “YuvaAI initiative for Skilling and Capacity Building”. This program aims to bridge the AI talent gap in the country by empowering 100,000 students and young developers aged to leverage open-source large language models (LLMs) to address real-world challenges. It aims to build capacity in generative AI skills, utilizing open-source LLMs while fostering AI innovation across key sectors. I bring up that acclaimed quote because composing prompts is both art and science.