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Last night’s The Last of Us finale on HBO Max ushered in the inevitable, the thing so many of us have feared for a decade: Major publications, the same ones who refer to video games as if they’re all still like Pac-Man, are weighing in on its controversial ending. Read more... View the full article

The second I saw The Last Spell’s first trailer back in 2021, I knew I had to play it. A city builder with Dungeons and Dragons-style units on an isometric battlefield where giant hordes of zombies are dispatched in turn-based tactics combat? And staged to a pulsing metal soundtrack? It seemed like an ingenious… Read more... View the full article

We are less than two weeks away from playing Capcom’s glorious repaint of its iconic third-person shooter, Resident Evil 4, originally released in 2005. Though breathless questions on sites like Reddit, Quora, and Twitter suggest the remake is still operating from the mysterious shadows, there’s a lot we know for… Read more... View the full article

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Last week Genna Bain, whose late husband was the game critic and YouTube personality John “Totalbiscuit” Bain, broke the news to fans that she’s contemplating removing all of his videos from the internet to prevent “AI” machine-learning technologies from storing and manipulating his voice to promote particular… Read more... View the full article

Dead Island 2, the open-world zombie RPG that passed through so many hands someone done forgot it in the development oven for over a decade, is finally coming out on April 21. This is a week earlier than originally anticipated, which we love to see. What’s funny, though, is that developer Dambuster Studios is out here… Read more... View the full article

The latest Pokémon Journeys: The Series episode just aired in Japan this Friday, and it has fans panicking. The anime is in its final season, and fans hoped that the most recent episode would satisfyingly wrap up Team Rocket’s story—but it was quite the opposite. Even Team Rocket’s haters feel that the villainous team… Read more... View the full article

GameStop’s Hollywood moment is finally coming this October. Sony announced its dramatization of the video game retailer’s meme stock explosion will hit theaters in October, starring Paul Dano, Seth Rogen, Pete Davidson and more. It’s called Dumb Money. I hope it lives up to it. Read more... View the full article

FromSoftware recently announced an expansion to its lauded open world game, which means the Elden Ring theorists have kicked into gear. Speculation has been running rampant ever since, and while we don’t 100% know who’s on the key art the developer released for Shadow of the Erdtree, the general consensus is that… Read more... View the full article

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Maybe you were wondering why Final Fantasy XVI, Square Enix’s highly anticipated action RPG, will only be available on PlayStation 5 when it launches on June 22. Well, according to Square Enix, it’s because of “the power of PlayStation 5" that lets the team achieve next-gen (when do we call it current-gen?) combat. Read more... View the full article

As an adaptation, HBO’s The Last of Us has been a fairly faithful recreation of Naughty Dog’s original game. However, during yesterday’s season one finale, “Look For The Light,” HBO’s series explored a character the game had only talked about in passing mentions. In doing so, the show reveals a long unanswered… Read more... View the full article

The mics were live and tape was rolling in the studio where the Miles Davis Quintet was recording dozens of tunes in 1956 for Prestige Records. When an engineer asked for the next song’s title, Davis shot back, “I’ll play it, and tell you what it is later.” Like the prolific jazz trumpeter and composer, researchers have been generating AI models at a feverish pace, exploring new architectures and use cases. Focused on plowing new ground, they sometimes leave to others the job of categorizing their work. A team of more than a hundred Stanford researchers collaborated to do just that in a 214-page paper released in the summer of 2021. In a 2021 paper, researchers reported that foundation models are finding a wide array of uses. They said transformer models, large language models (LLMs) and other neural networks still being built are part of an important new category they dubbed foundation models. Foundation Models Defined A foundation model is an AI neural network — trained on mountains of raw data, generally with unsupervised learning — that can be adapted to accomplish a broad range of tasks, the paper said. “The sheer scale and scope of foundation models from the last few years have stretched our imagination of what’s possible,” they wrote. Two important concepts help define this umbrella category: Data gathering is easier, and opportunities are as wide as the horizon. No Labels, Lots of Opportunity Foundation models generally learn from unlabeled datasets, saving the time and expense of manually describing each item in massive collections. Earlier neural networks were narrowly tuned for specific tasks. With a little fine-tuning, foundation models can handle jobs from translating text to analyzing medical images. Foundation models are demonstrating “impressive behavior,” and they’re being deployed at scale, the group said on the website of its research center formed to study them. So far, they’ve posted more than 50 papers on foundation models from in-house researchers alone. “I think we’ve uncovered a very small fraction of the capabilities of existing foundation models, let alone future ones,” said Percy Liang, the center’s director, in the opening talk of the first workshop on foundation models. AI’s Emergence and Homogenization In that talk, Liang coined two terms to describe foundation models: Emergence refers to AI features still being discovered, such as the many nascent skills in foundation models. He calls the blending of AI algorithms and model architectures homogenization, a trend that helped form foundation models. (See chart below.) The field continues to move fast. A year after the group defined foundation models, other tech watchers coined a related term — generative AI. It’s an umbrella term for transformers, large language models, diffusion models and other neural networks capturing people’s imaginations because they can create text, images, music, software and more. Generative AI has the potential to yield trillions of dollars of economic value, said executives from the venture firm Sequoia Capital who shared their views in a recent AI Podcast. A Brief History of Foundation Models “We are in a time where simple methods like neural networks are giving us an explosion of new capabilities,” said Ashish Vaswani, an entrepreneur and former senior staff research scientist at Google Brain who led work on the seminal 2017 paper on transformers. That work inspired researchers who created BERT and other large language models, making 2018 “a watershed moment” for natural language processing, a report on AI said at the end of that year. Google released BERT as open-source software, spawning a family of follow-ons and setting off a race to build ever larger, more powerful LLMs. Then it applied the technology to its search engine so users could ask questions in simple sentences. In 2020, researchers at OpenAI announced another landmark transformer, GPT-3. Within weeks, people were using it to create poems, programs, songs, websites and more. “Language models have a wide range of beneficial applications for society,” the researchers wrote. Their work also showed how large and compute-intensive these models can be. GPT-3 was trained on a dataset with nearly a trillion words, and it sports a whopping 175 billion parameters, a key measure of the power and complexity of neural networks. The growth in compute demands for foundation models. (Source: GPT-3 paper) “I just remember being kind of blown away by the things that it could do,” said Liang, speaking of GPT-3 in a podcast. The latest iteration, ChatGPT — trained on 10,000 NVIDIA GPUs — is even more engaging, attracting over 100 million users in just two months. Its release has been called the iPhone moment for AI because it helped so many people see how they could use the technology. One timeline describes the path from early AI research to ChatGPT. (Source: blog.bytebytego.com) From Text to Images About the same time ChatGPT debuted, another class of neural networks, called diffusion models, made a splash. Their ability to turn text descriptions into artistic images attracted casual users to create amazing images that went viral on social media. The first paper to describe a diffusion model arrived with little fanfare in 2015. But like transformers, the new technique soon caught fire. Researchers posted more than 200 papers on diffusion models last year, according to a list maintained by James Thornton, an AI researcher at the University of Oxford. In a tweet, Midjourney CEO David Holz revealed that his diffusion-based, text-to-image service has more than 4.4 million users. Serving them requires more than 10,000 NVIDIA GPUs mainly for AI inference, he said in an interview (subscription required). Dozens of Models in Use Hundreds of foundation models are now available. One paper catalogs and classifies more than 50 major transformer models alone (see chart below). The Stanford group benchmarked 30 foundation models, noting the field is moving so fast they did not review some new and prominent ones. Startup NLP Cloud, a member of the NVIDIA Inception program that nurtures cutting-edge startups, says it uses about 25 large language models in a commercial offering that serves airlines, pharmacies and other users. Experts expect that a growing share of the models will be made open source on sites like Hugging Face’s model hub. Experts note a rising trend toward releasing foundation models as open source. Foundation models keep getting larger and more complex, too. That’s why — rather than building new models from scratch — many businesses are already customizing pretrained foundation models to turbocharge their journeys into AI. Foundations in the Cloud One venture capital firm lists 33 use cases for generative AI, from ad generation to semantic search. Major cloud services have been using foundation models for some time. For example, Microsoft Azure worked with NVIDIA to implement a transformer for its Translator service. It helped disaster workers understand Haitian Creole while they were responding to a 7.0 earthquake. In February, Microsoft announced plans to enhance its browser and search engine with ChatGPT and related innovations. “We think of these tools as an AI copilot for the web,” the announcement said. Google announced Bard, an experimental conversational AI service. It plans to plug many of its products into the power of its foundation models like LaMDA, PaLM, Imagen and MusicLM. “AI is the most profound technology we are working on today,” the company’s blog wrote. Startups Get Traction, Too Startup Jasper expects to log $75 million in annual revenue from products that write copy for companies like VMware. It’s leading a field of more than a dozen companies that generate text, including Writer, an NVIDIA Inception member. Other Inception members in the field include Tokyo-based rinna that’s created chatbots used by millions in Japan. In Tel Aviv, Tabnine runs a generative AI service that’s automated up to 30% of the code written by a million developers globally. A Platform for Healthcare Researchers at startup Evozyne used foundation models in NVIDIA BioNeMo to generate two new proteins. One could treat a rare disease and another could help capture carbon in the atmosphere. Evozyne and NVIDIA described a hybrid foundation model for creating proteins in a joint paper. BioNeMo, a software platform and cloud service for generative AI in drug discovery, offers tools to train, run inference and deploy custom biomolecular AI models. It includes MegaMolBART, a generative AI model for chemistry developed by NVIDIA and AstraZeneca. “Just as AI language models can learn the relationships between words in a sentence, our aim is that neural networks trained on molecular structure data will be able to learn the relationships between atoms in real-world molecules,” said Ola Engkvist, head of molecular AI, discovery sciences and R&D at AstraZeneca, when the work was announced. Separately, the University of Florida’s academic health center collaborated with NVIDIA researchers to create GatorTron. The large language model aims to extract insights from massive volumes of clinical data to accelerate medical research. A Stanford center is applying the latest diffusion models to advance medical imaging. NVIDIA also helps healthcare companies and hospitals use AI in medical imaging, speeding diagnosis of deadly diseases. AI Foundations for Business Another new framework, NVIDIA NeMo Megatron, aims to let any business create its own billion- or trillion-parameter transformers to power custom chatbots, personal assistants and other AI applications. It created the 530-parameter Megatron-Turing Natural Language Generation model (MT-NLG) that powers TJ, the Toy Jensen avatar that gave part of the keynote at NVIDIA GTC last year. Foundation models — connected to 3D platforms like NVIDIA Omniverse — will be key to simplifying development of the metaverse, the 3D evolution of the internet. These models will power applications and assets for entertainment and industrial users. Factories and warehouses are already applying foundation models inside digital twins, realistic simulations that help find more efficient ways to work. Foundation models can ease the job of training autonomous vehicles and robots that assist humans on factory floors and logistics centers like the one described below. New uses for foundation models are emerging daily, as are challenges in applying them. Several papers on foundation and generative AI models describing risks such as: amplifying bias implicit in the massive datasets used to train models, introducing inaccurate or misleading information in images or videos, and violating intellectual property rights of existing works. “Given that future AI systems will likely rely heavily on foundation models, it is imperative that we, as a community, come together to develop more rigorous principles for foundation models and guidance for their responsible development and deployment,” said the Stanford paper on foundation models. Current ideas for safeguards include filtering prompts and their outputs, recalibrating models on the fly and scrubbing massive datasets. “These are issues we’re working on as a research community,” said Bryan Catanzaro, vice president of applied deep learning research at NVIDIA. “For these models to be truly widely deployed, we have to invest a lot in safety.” It’s one more field AI researchers and developers are plowing as they create the future. View the full article

A classic bank run caused Silicon Valley Bank to become the second-largest bank collapse in history. Now the Federal Reserve is promising a bailout for all of its customers, which includes everyone from small startups to major tech industry players. Roblox, the social media platform where millions of kids play potato… Read more... View the full article

Welcome to Exp. Share, Kotaku’s Pokémon column in which we dive deep to explore notable characters, urban legends, communities, and just plain weird quirks from throughout the Pokémon franchise. This week, we’re taking a look at the upcoming 3DS and Wii U eShop shutdowns and the effect they will have on the series. Read more... View the full article

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Well, friends. We’ve come to the end of the road, at least for now. Episode nine of HBO’s The Last of Us is the season finale, bringing us to the end of the story told in the first game. Even the episode’s title, “Look for the Light,” neatly closes the loop opened by that of the first episode, “When You’re Lost In the… Read more... View the full article

[The following will contain spoilers for The Last of Us show and both video games] Read more... View the full article

Hello Fred171, Welcome to UnityHQ Nolfseries Community. Please feel free to browse around and get to know the others. If you have any questions please don't hesitate to ask. Fred171 joined on the 03/11/2023. View Member

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10 years ago, The Last of Us’ unexpected and morally divisive ending made history. Choosing to land in a place of uncertainty, the conclusion bucked what many other games chose to do, and often still do: present a straightforward, neat, conventionally satisfying end where the good guys are the good guys and the bad… Read more... View the full article

Nine years ago, Super Mario 64 player toyuru2 wall-jumped his way up the slide in Cool, Cool Mountain, sending the plumber into the void–but not before grabbing a 1-up mushroom. At the time, it was a feat, as nobody had ever gotten the mushroom. But then, a new challenge emerged: was it possible to grab the mushroom… Read more... View the full article

Hello fogstank1, Welcome to UnityHQ Nolfseries Community. Please feel free to browse around and get to know the others. If you have any questions please don't hesitate to ask. fogstank1 joined on the 03/11/2023. View Member

Have you ever waited for a few hours to ride a popular roller coaster? Perhaps. But I can guarantee you that nobody has ever waited the entire life of the known universe. Well, unless you are the unlucky digital folks stuck on a new wild and complicated Roller Coaster Tycoon 2 creation from YouTuber Marcel Vos. Read more... View the full article

Like most people who require water to live, you probably like H20 a normal amount—but you definitely don’t like water as much as this famous Nintendo fan. They’re so well-known and beloved that they’ve even been featured in the official plumber website for the Super Mario Bros. movie. Read more... View the full article