Рубрика: AI

As the Metaverse takes shape and is revolutionizing social media in fascinating new ways, AI influencers are becoming more well-known. These so-called AI influencers are incredibly realistic, and are altering our perception of computer generation by bridging the gap between digital and real life.

Technological developments in AI, particularly in the areas of text-to-images, alongside the rise of models such as Stable Diffusion, DALL.E 2, and now Imagen 2, have made it possible for creators to build hyper-realistic figures with distinct personalities, styles, and even ideals. These influencers, who blur the boundaries between fantasy and reality, have won the hearts and minds of people all over the world.
Let’s take a look at the top 11 AI influencers on Instagram that are revolutionising marketing for brands and companies, alongside reviewing tech products, software tips, and are pretty much resonating well with the vast majority of the audience.

Lu do Magalu @magazineluiza

6.4 Million Followers

Top AI influencer Lu from Brazil shares her lifestyle content, which includes unboxings and product reviews. Even though the majority of her audience is still in her native nation, she has a devoted following that doesn’t appear to be diminishing.

Lil Miquela @lilmiquela

2.7 Million Followers

Lil Miquella, arguably the most well-known AI influencer globally, was listed among Time Magazine’s “25 Most Influential People on the Internet.” She has collaborated with some of the greatest businesses in the world and is well-known for her music, advocacy, and stunning style.

Janky & Guggimon @jankyandguggimon

1 Million Followers

Guggimon is a lively influencer with a carefree attitude, much like his close friend Janky. Posting about his crazy exploits, including walking the red carpet, having a good time, and getting into mischief, doesn’t scare him.

O Surreal Mundo de Any Malu @anymalu_real

667 K Followers

Any Malu is an influencer with a cartoon aesthetic who consistently delivers relatable material that her fans adore. Observe her relationships and day-to-day activities as you share in her numerous travels.

K/DA @kda_music

522 K Followers

KAI’SA, Ahri, Evelynn, and Akali are the four virtual stars that comprise the Los Angeles-based girl quartet K/DA. Every major streaming platform has their music available, and the group has a distinctive and exciting look and feel thanks to the individual styles of each member!

Thalaysia Pov @thalasya_

461 K Followers

As the first metahuman from Indonesia, Thalaysia takes great pride in exhibiting the splendor of her culture. While sharing gorgeous pictures of her everyday activities and social contacts, she is trying to establish herself as a recording artist.

Noonoouri @noonoouri

424 K Followers

Noonoouri hails from Munich and uses her platform to highlight social issues. As a vegan activist, this 19-year-old model has already worked with brands like Balenciaga, Off White, and Versace, showing age is only a number.

Leya Love @leyalovenature

412 K Followers

Leya is committed to spreading love and harmony around the world, and she accomplishes this by sharing inspiring and upbeat content. She is a supporter of the World Awareness Movement and utilizes her platform to share breathtaking images of the planet’s natural beauty, including landscapes, wildlife, and people. She thinks that love has the power to transform the world.

Imma Gram (@imma.gram)

395 K Followers

As Japan’s first virtual model, Imma stands out as a fun and curious personality that lives life to the fullest. Her passion for art, fashion, Japanese culture, and films is apparent in her feed, and her unique postings delight her followers. Imma has worked with some of the world’s largest brands, like Nike, Valentino, Adidas, and Amazon!

Qai Qai @realqaiqai

341 K Followers

Who says babies can’t make a name for themselves? Qai Qai may be little, but her follower count is impressive! We just can’t get enough of her dances, lip-syncing, and entertaining personality, all bundled up into a ribbon-topped, pint-sized body!

Bermuda @bermudaisbae

236 K Followers

Bermuda is a fashion icon, using her platform to post stunning pictures her followers adore. Picturing everything from her workouts to high-fashion events and hanging out with friends, she’s the perfect mix of relatable and life goals!

The post 11 AI Influencers to Follow on Instagram in 2024 appeared first on Analytics India Magazine.

Just as expected, Intel has announced the launch of AI PCs, to build and run AI on every PC. Pat Gelsinger, CEO of Intel, at the AI Everywhere event announced the company’s partnership with Dell, HP, Lenovo, Supermicro, and Microsoft for onboarding the chips on their devices.

This is made possible by the Intel Core Ultra chips announced at the event along with the Intel Arc GPUs. Featuring a maximum of 8 XE GPU cores, the performance is akin to having an integrated Intel Arc 370M discrete GPU directly within the processor, albeit without the presence of dedicated video memory.

The announcement, first made at Intel Innovations a couple of months ago, highlights the processors as the company’s pioneering venture into incorporating a neural processing unit (NPU) into their chips.

Gelsinger added that Intel is dedicated to developing technologies that enable seamless integration and efficient operation of AI across various applications, both in the cloud and increasingly on local devices such as PCs and edge devices.

“We think 2024 marks the era of AI PC and that will be the star of the show in this coming year,” said Gelsinger.

The AI PC concept aims to bring AI capabilities directly to personal computers, allowing users to run generative AI chatbots, like ChatGPT, locally, without relying on cloud data centres, and even for inference models such as Llama 2. This development is particularly significant for enhancing data security, a crucial aspect for business and enterprise users.

Intel aims to deliver 100 million client processors, which is five times more than any of the competitors.

Furthermore, the Core Ultra processors bring about a paradigm shift with three major architectural features introduced to Intel’s laptop portfolio. Firstly, there is a departure from the conventional single-silicon-die design to a multi-chiplet-module (MCM) design. This novel approach involves bonding several smaller silicon chiplets together to create a single chip, offering increased versatility in chip functionality compared to previous processor generations.

AMD also announced at its Advancing AI event that it’s AI PC idea by partnering with Microsoft, Meta, and several OEM companies. At the AMD Advancing AI event, the company has unveiled various lines of AI announcements including the Instinct MI300X AI accelerators to compete with NVIDIA H100, updates to ROCm, and Ryzen AI PCs for on-device computing.

The post Intel Releases Core Ultra, Arc GPUs for Bringing AI to Every PC appeared first on Analytics India Magazine.

OpenAI had to close to new ChatGPT Plus subscriptions just days after its developers' conference, DevDay. Since then, anyone who wanted to sign up for ChatGPT Plus had to sign up for a waitlist — until now. OpenAI just reopened ChatGPT Plus subscriptions for anyone who wants to sign up; no waiting necessary.

"We have re-enabled ChatGPT Plus subscriptions!" OpenAI's CEO, Sam Altman, announced on X, formerly Twitter. "Thanks for your patience while we found more GPUs."

Also: How to use ChatGPT Plus: From web browsing to plugins

Graphics Processing Units (GPUs) enhance an AI chatbot's computational power and parallel processing capabilities. They're optimized to handle thousands of threads simultaneously, achieve better scalability, and improve a chatbot's machine-learning capabilities for faster and more efficient training.

Essentially, GPUs can help expand an AI chatbot's capacity to handle more queries from more users at any given time. Additional GPUs also reduce response latency or the time the bot responds to users.

ChatGPT Plus subscriptions cost $20 a month and give users access to GPT-4, OpenAI's most powerful large language model (LLM) that can also browse the internet with BIng, generate images thanks to DALL-E 3, and perform advanced data analysis. The Plus tier also gives subscribers access to My GPTs, which are custom AI chatbots powered by GPT-4 and plugins.

Also: GPT-3.5 vs GPT-4: Is ChatGPT Plus worth its subscription fee?

Non-subscribing users still have access to the free version of ChatGPT, which is powered by the GPT-3.5 model and can perform text generation.

OpenAI thinks superhuman AI is coming — and wants to build tools to control it Kyle Wiggers 9 hours

While investors were preparing to go nuclear after Sam Altman’s unceremonious ouster from OpenAI and Altman was plotting his return to the company, the members of OpenAI’s Superalignment team were assiduously plugging along on the problem of how to control AI that’s smarter than humans.

Or at least, that’s the impression they’d like to give.

This week, I took a call with three of the Superalignment team’s members — Collin Burns, Pavel Izmailov and Leopold Aschenbrenner — who were in New Orleans at NeurIPS, the annual machine learning conference, to present OpenAI’s newest work on ensuring that AI systems behave as intended.

OpenAI formed the Superalignment team in July to develop ways to steer, regulate and govern “superintelligent” AI systems — that is, theoretical systems with intelligence far exceeding that of humans.

“Today, we can basically align models that are dumber than us, or maybe around human-level at most,” Burns said. “Aligning a model that’s actually smarter than us is much, much less obvious — how we can even do it?”

The Superalignment effort is being led by OpenAI co-founder and chief scientist Ilya Sutskever, which didn’t raise eyebrows in July — but certainly does now in light of the fact that Sutskever was among those who initially pushed for Altman’s firing. While some reporting suggests Sutskever is in a “state of limbo” following Altman’s return, OpenAI’s PR tells me that Sutskever is indeed — as of today, at least — still heading the Superalignment team.

Superalignment is a bit of touchy subject within the AI research community. Some argue that the subfield is premature; others imply that it’s a red herring.

While Altman has invited comparisons between OpenAI and the Manhattan Project, going so far as to assemble a team to probe AI models to protect against “catastrophic risks” including chemical and nuclear threats, some experts say that there’s little evidence to suggest the startup’s technology will gain world-ending, human-outsmarting capabilities anytime soon — or ever. Claims of imminent superintelligence, these experts add, serve only to deliberately draw attention away from and distract from the pressing AI regulatory issues of the day, like algorithmic bias and AI’s tendency toward toxicity.

For what it’s worth, Suksever appears to believe earnestly that AI — not OpenAI’s per se, but some embodiment of it — could someday pose an existential threat. He reportedly went so far as to commission and burn a wooden effigy at a company offsite to demonstrate his commitment to preventing AI harm from befalling humanity, and commands a meaningful amount of OpenAI’s compute — 20% of its existing computer chips — for the Superalignment’s team’s research.

“AI progress recently has been extraordinarily rapid, and I can assure you that it’s not slowing down,” Aschenbrenner said. “I think we’re going to reach human-level systems pretty soon, but it won’t stop there — we’re going to go right through to superhuman systems … So how do we align superhuman AI systems and make them safe? It’s really a problem for all of humanity — perhaps the most important unsolved technical problem of our time.”

The Superalignment team, currently, is attempting to build governance and control frameworks that might apply well to future powerful AI systems. It’s not a straightforward task considering that the definition of “superintelligence” — and whether a particular AI system has achieved it — is the subject of robust debate. But the approach the team’s settled on for now involves using a weaker, less-sophisticated AI model (e.g. GPT-2) to guide a more advanced, sophisticated model (GPT-4) in desirable directions — and away from undesirable ones.

A figure illustrating the Superalignment team’s AI-based analogy for aligning superintelligent systems.

“A lot of what we’re trying to do is tell a model what to do and ensure it will do it,” Burns said. “How do we get a model to follow instructions and get a model to only help with things that are true and not make stuff up? How do we get a model to tell us if the code it generated is safe or egregious behavior? These are the types of tasks we want to be able to achieve with our research.”

But wait, you might say — what does AI guiding AI have to do with preventing humanity-threatening AI? Well, it’s an analogy: the weak model is meant to be a stand-in for human supervisors while the strong model represents superintelligent AI. Similar to humans who might not be able to make sense of a superintelligent AI system, the weak model can’t “understand” all the complexities and nuances of the strong model — making the setup useful for proving out superalignment hypotheses, the Superalignment team says.

“You can think of sixth-grade student trying to supervise a college student,” Izmailov explained. “Let’s say the sixth grader is trying to tell the college student about a task that he kind of knows how to solve … Even though the supervision from the sixth grader can have mistakes in the details, there’s hope that the college student would understand the gist and would be able to do the task better than the supervisor.”

In the Superalignment team’s setup, a weak model fine-tuned on a particular task generates labels that are used to “communicate” the broad strokes of that task to the strong model. Given these labels, the strong model can generalize more or less correctly according to the weak model’s intent — even if the weak model’s labels contain errors and biases, the team found.

The weak-strong model approach might even lead to breakthroughs in the area of hallucinations, claims the team.

“Hallucinations are actually quite interesting, because internally, the model actually knows whether the thing it’s saying is fact or fiction,” Aschenbrenner said. “But the way these models are trained today, human supervisors reward them ‘thumbs up,’ ‘thumbs down’ for saying things. So sometimes, inadvertently, humans reward the model for saying things that are either false or that the model doesn’t actually know about and so on. If we’re successful in our research, we should develop techniques where we can basically summon the model’s knowledge and we could apply that summoning on whether something is fact or fiction and use this to reduce hallucinations.”

But the analogy isn’t perfect. So OpenAI wants to crowdsource ideas.

To that end, OpenAI is launching a $10 million grant program to support technical research on superintelligent alignment, tranches of which will be reserved for academic labs, nonprofits, individual researchers and graduate students. OpenAI also plans to also host an academic conference on superalignment in early 2025, where it’ll share and promote the superalignment prize finalists’ work.

Curiously, a portion of funding for the grant will come from former Google CEO and chairman Eric Schmidt. Schmidt — an ardent supporter of Altman — is fast becoming a poster child for AI doomerism, asserting the arrival of dangerous AI systems is nigh and that regulators aren’t doing enough in preparation. It’s not out of a sense of altruism, necessarily — reporting in Protocol and Wired note that Schmidt, an active AI investor, stands to benefit enormously commercially if the U.S. government were to implement his proposed blueprint to bolster AI research.

The donation might be perceived as virtue signaling through a cynical lens, then. Schmidt’s personal fortune stands around an estimated $24 billion, and he’s poured hundreds of millions into other, decidedly less ethics-focused AI ventures and funds — including his own.

Schmidt denies this is the case, of course.

“AI and other emerging technologies are reshaping our economy and society,” he said in an emailed statement. “Ensuring they are aligned with human values is critical, and I am proud to support OpenAI’s new [grants] to develop and control AI responsibly for public benefit.”

Indeed, the involvement of a figure with such transparent commercial motivations begs the question: will OpenAI’s superalignment research as well as the research it’s encouraging the community to submit to its future conference be made available for anyone to use as they see fit?

The Superalignment team assured me that, yes, both OpenAI’s research — including code — and the work of others who receive grants and prizes from OpenAI on superalignment-related work will be shared publicly. We’ll hold the company to it.

“Contributing not just to the safety of our models but the safety of other labs’ models and advanced AI in general is a part of our mission,” Aschenbrenner said. “It’s really core to our mission of building [AI] for the benefit of all of humanity, safely. And we think that doing this research is absolutely essential for making it beneficial and making it safe.”

Stability AI has officially announced its Stability AI Membership. The membership structure introduces three tiers catering to a diverse user base, ranging from individual enthusiasts to Fortune 500 companies.

The first tier, Non-Commercial, is available at no cost for personal use and research, providing access to the complete suite of core models

Launching Stability AI memberships for flat rate commercial use of our new core models.
Free for personal/research use, $20 a month for up to $1m revenue/funding or 1m users, grants available
Figuring out pricing above trying to keep it simple.
Please do give feedback https://t.co/D6NN8Arw7I

— Emad @ NeurIPS (@EMostaque) December 14, 2023

The Professional tier, priced at $20 USD per month, targets creators, developers, and startups, offering self-hosted, commercial usage of core models and access to an exclusive Discord community. Discounts are available for those facing financial constraints.

The Enterprise tier, designed for larger companies with custom pricing, encompasses benefits from the Professional tier and the option to incorporate additional enterprise features, such as support and solutions engineering.

Customers have multiple deployment options, including the membership, self-serve API Developer Platform, or through cloud service provider partners. Previous model releases may have separate licenses, accessible on Hugging Face.

Stability AI aims to make state-of-the-art generative AI technology accessible to all while

sustaining affordability. The company emphasises its commitment to promoting innovative and accessible technological advancements, empowering professionals and creatives.

The membership not only focuses on accessibility but also prioritises safety, privacy, and security. By providing flexible and controllable solutions, Stability AI enables users to scale and innovate while retaining full control of their data and products within their environment.

Stability AI has announced its membership program amid financial challenges, prompting investor pressure for a potential sale and urging its chief, Emad Mostaque, to step down.

The company generated $1.2 million in revenue in August and was projected to reach $3 million this month from software and services, according to a post by Mostaque on X which he later deleted.

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At the Intel AI Everywhere event, the company has revealed the forthcoming release of 5th Gen Xeon processors, featuring AI acceleration in every core and expected to hit the market in 2024. Unveiled by Intel CEO Pat Gelsinger, these processors, previously codenamed Emerald Rapids, mark a significant advancement in computing.

Designed to cater to AI, high-performance computing, networking, storage, databases, and security needs, they aim to enhance performance while minimising the total cost of ownership (TCO).

Intel Xeon powered data centres would be used by Microsoft, Google Cloud, and IBM, and many more would integrate them.

Sandra Rivera, Intel’s executive vice president and general manager of Data Center and AI Group, underscored the importance of this development. “Built for AI, our 5th Gen Intel Xeon processors provide greater performance to customers deploying AI capabilities across cloud, network, and edge use cases. We’re launching 5th Gen Intel Xeon on a proven foundation that will enable rapid adoption and scale at lower TCO,” she stated.

Key features of the 5th Gen Xeon processors include AI acceleration in every core, optimizing them for AI workloads and delivering up to 42% higher inference performance with minimal latency on large language models. This enables end-to-end AI processing without the need for additional accelerators, making AI tasks more efficient.

In terms of general compute performance, the processors offer an average gain of 21% compared to the previous generation. They also boast a 36% increase in performance per watt across various customer workloads, translating to significant efficiency improvements.

These processors support up to 64 cores per CPU, enhanced last-level cache, eight channels of DDR5, and higher memory transfer speeds. These improvements contribute to overall enhanced performance and bandwidth. Additionally, they ensure compatibility with CXL Type 3 workflows through leading cloud service providers.

Furthermore, the processors come equipped with security enhancements, featuring Intel Trust Domain Extensions (Intel TDX). This provides increased confidentiality and security at the VM level, ensuring enhanced privacy and control over data.

Looking ahead, the 5th Gen Xeon processors, which are pin-compatible with the previous generation, are set to be available in single- and dual-socket systems from leading OEMs such as Cisco, Dell, HPE, Lenovo, and others by the first quarter of 2024. Major cloud service providers will announce the availability of instances based on these processors throughout the year.

Intel remains committed to its roadmap, with plans to introduce Sierra Forest, emphasising E-core efficiency with up to 288 cores, in the first half of 2024. Following closely will be Granite Rapids, focusing on P-core performance.

The company has also announced the launch of AI PCs, to build and run AI on every PC. Gelsinger announced the company’s partnership with Dell, HP, Lenovo, Supermicro, and Microsoft for onboarding the chips on their devices.

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AI isn’t and won’t soon be evil or even smart, but it’s also irreversibly pervasive Darrell Etherington @etherington / 9 hours

Artificial intelligence – or rather, the variety based on large language models we’re currently enthralled with – is already in the autumn of its hype cycle, but unlike crypto, it won’t just disappear into the murky, undignified corners of the internet once its ‘trend’ status fades. Instead, it’s settling into a place where its use is already commonplace, even for purposes for which it’s frankly ill-suited. Doomerism would you have you believe that AI will get so smart it’ll enslave or sunset humanity, but the reality is that it’s much more threatening as an omnipresent layer of error and hallucinations that seep into our shared intellectual groundwater.

The doomerism vs. e/acc debate continues apace, with all the grounded, fact-based arguments on either side that you can expect from the famously down-to-earth Silicon Valley elites. Key context for any of these figures of influence is to remember that they spend their entire careers lauding/decrying the extreme success of failure of whatever tech they’re betting on or against – only to have said technology usually fizzle well-short of ether the perfect or the catastrophic state. Witness everything always, forever, but if you’re looking for specifics, self-driving is a very handy recent one, as is VR and the metaverse.

Utopian vs. dystopian debates in tech always do what they’re actually intended to do, which is distract from having real conversations about the real, current-day impact of technology as it’s actually deployed and used. AI has undoubtedly had a massive impact, particularly since the introduction of ChatGPT just over a year ago, but that impact isn’t about whether we’ve unwittingly sown the seeds for a virtual deity, it’s about how ChatGPT proved far more popular, more viral and more sticky than its creators ever thought possible – even while its capabilities actually matched their relatively humble expectations.

Use of generative AI, according to most recent studies, is fairly prevalent and growing, especially among younger users. The leading uses aren’t novelty or fun, per a recent Salesforce study of use over the past year; instead, it’s overwhelmingly being used to automate work-based tasks and communications. With a few rare exceptions like when it’s used for preparing legal arguments, the consequences of some light AI hallucination in generating these communications and corporate drudgery are insignificant, but it’s also undoubtedly resulting in a digital strata that consists of easy-to-miss factual errors and minor inaccuracies.

That’s not to say people are particularly good at disseminating information free of factual error; rather the opposite, actually, as we’ve seen via the rise of the misinformation economy on social networks, particularly in the years leading up to and including the Trump presidency. Even leaving aside malicious agendas and intentional acts, error is just a baked in part of human belief and communication, and as such has always pervaded shared knowledge pools.

The difference is that LLM-based AI models do so casually, constantly, and without self-reflection, and that they do so with a sheen of authoritative confidence which users are susceptible to because of many years of relatively stable, factual and reliable Google search results (admittedly, ‘relatively’ is doing a lot of work here). Early on, search results and crowdsourced online pools of information were treated with a healthy dose of critical skepticism, but years or even decades of fairly reliable info delivered by Google search, Wikipedia and the like has short-circuited our distrust of things that come back when we type a query into a text box on the internet.

I think the results of having ChatGPT and its ilk producing a massive volume of content with questionable accuracy for menial everyday communication will be subtle, but they’re worth investigating and potentially mitigating, too. The first step would be examining why people feel like they can entrust so much of this stuff to AI in its current state to begin with; with any widespread task automation, the primary focus of inquiry should probably be on the task, not the automation. Either way, though, the real, impactful big changes that AI brings are already here, and while they don’t look anything like Skynet, they’re more worthy of study than possibilities that rely on techno-optimistic dreams coming true.