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Tag: open source

  • Inside the Creation of DBRX, the World’s Most Powerful Open Source AI Model

    Inside the Creation of DBRX, the World’s Most Powerful Open Source AI Model

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    This past Monday, about a dozen engineers and executives at data science and AI company Databricks gathered in conference rooms connected via Zoom to learn if they had succeeded in building a top artificial intelligence language model. The team had spent months, and about $10 million, training DBRX, a large language model similar in design to the one behind OpenAI’s ChatGPT. But they wouldn’t know how powerful their creation was until results came back from the final tests of its abilities.

    “We’ve surpassed everything,” Jonathan Frankle, chief neural network architect at Databricks and leader of the team that built DBRX, eventually told the team, which responded with whoops, cheers, and applause emojis. Frankle usually steers clear of caffeine but was taking sips of iced latte after pulling an all-nighter to write up the results.

    Databricks will release DBRX under an open source license, allowing others to build on top of its work. Frankle shared data showing that across about a dozen or so benchmarks measuring the AI model’s ability to answer general knowledge questions, perform reading comprehension, solve vexing logical puzzles, and generate high-quality code, DBRX was better than every other open source model available.

    Four people standing at the corner of a grey and yellow wall in an office space

    AI decision makers: Jonathan Frankle, Naveen Rao, Ali Ghodsi, and Hanlin Tang.Photograph: Gabriela Hasbun

    It outshined Meta’s Llama 2 and Mistral’s Mixtral, two of the most popular open source AI models available today. “Yes!” shouted Ali Ghodsi, CEO of Databricks, when the scores appeared. “Wait, did we beat Elon’s thing?” Frankle replied that they had indeed surpassed the Grok AI model recently open-sourced by Musk’s xAI, adding, “I will consider it a success if we get a mean tweet from him.”

    To the team’s surprise, on several scores DBRX was also shockingly close to GPT-4, OpenAI’s closed model that powers ChatGPT and is widely considered the pinnacle of machine intelligence. “We’ve set a new state of the art for open source LLMs,” Frankle said with a super-sized grin.

    Building Blocks

    By open-sourcing, DBRX Databricks is adding further momentum to a movement that is challenging the secretive approach of the most prominent companies in the current generative AI boom. OpenAI and Google keep the code for their GPT-4 and Gemini large language models closely held, but some rivals, notably Meta, have released their models for others to use, arguing that it will spur innovation by putting the technology in the hands of more researchers, entrepreneurs, startups, and established businesses.

    Databricks says it also wants to open up about the work involved in creating its open source model, something that Meta has not done for some key details about the creation of its Llama 2 model. The company will release a blog post detailing the work involved to create the model, and also invited WIRED to spend time with Databricks engineers as they made key decisions during the final stages of the multimillion-dollar process of training DBRX. That provided a glimpse of how complex and challenging it is to build a leading AI model—but also how recent innovations in the field promise to bring down costs. That, combined with the availability of open source models like DBRX, suggests that AI development isn’t about to slow down any time soon.

    Ali Farhadi, CEO of the Allen Institute for AI, says greater transparency around the building and training of AI models is badly needed. The field has become increasingly secretive in recent years as companies have sought an edge over competitors. Opacity is especially important when there is concern about the risks that advanced AI models could pose, he says. “I’m very happy to see any effort in openness,” Farhadi says. “I do believe a significant portion of the market will move towards open models. We need more of this.”

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  • The Dark Side of Open Source AI Image Generators

    The Dark Side of Open Source AI Image Generators

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    Whether through the frowning high-definition face of a chimpanzee or a psychedelic, pink-and-red-hued doppelganger of himself, Reuven Cohen uses AI-generated images to catch people’s attention. “I’ve always been interested in art and design and video and enjoy pushing boundaries,” he says—but the Toronto-based consultant, who helps companies develop AI tools, also hopes to raise awareness of the technology’s darker uses.

    “It can also be specifically trained to be quite gruesome and bad in a whole variety of ways,” Cohen says. He’s a fan of the freewheeling experimentation that has been unleashed by open source image-generation technology. But that same freedom enables the creation of explicit images of women used for harassment.

    After nonconsensual images of Taylor Swift recently spread on X, Microsoft added new controls to its image generator. Open source models can be commandeered by just about anyone and generally come without guardrails. Despite the efforts of some hopeful community members to deter exploitative uses, the open source free-for-all is near-impossible to control, experts say.

    “Open source has powered fake image abuse and nonconsensual pornography. That’s impossible to sugarcoat or qualify,” says Henry Ajder, who has spent years researching harmful use of generative AI.

    Ajder says that at the same time that it’s becoming a favorite of researchers, creatives like Cohen, and academics working on AI, open source image generation software has become the bedrock of deepfake porn. Some tools based on open source algorithms are purpose-built for salacious or harassing uses, such as “nudifying” apps that digitally remove women’s clothes in images.

    But many tools can serve both legitimate and harassing use cases. One popular open source face-swapping program is used by people in the entertainment industry and as the “tool of choice for bad actors” making nonconsensual deepfakes, Ajder says. High-resolution image generator Stable Diffusion, developed by startup Stability AI, is claimed to have more than 10 million users and has guardrails installed to prevent explicit image creation and policies barring malicious use. But the company also open sourced a version of the image generator in 2022 that is customizable, and online guides explain how to bypass its built-in limitations.

    Meanwhile, smaller AI models known as LoRAs make it easy to tune a Stable Diffusion model to output images with a particular style, concept, or pose—such as a celebrity’s likeness or certain sexual acts. They are widely available on AI model marketplaces such as Civitai, a community-based site where users share and download models. There, one creator of a Taylor Swift plug-in has urged others not to use it “for NSFW images.” However, once downloaded, its use is out of its creator’s control. “The way that open source works means it’s going to be pretty hard to stop someone from potentially hijacking that,” says Ajder.

    4chan, the image-based message board site with a reputation for chaotic moderation is home to pages devoted to nonconsensual deepfake porn, WIRED found, made with openly available programs and AI models dedicated solely to sexual images. Message boards for adult images are littered with AI-generated nonconsensual nudes of real women, from porn performers to actresses like Cate Blanchett. WIRED also observed 4chan users sharing workarounds for NSFW images using OpenAI’s Dall-E 3.

    That kind of activity has inspired some users in communities dedicated to AI image-making, including on Reddit and Discord, to attempt to push back against the sea of pornographic and malicious images. Creators also express worry about the software gaining a reputation for NSFW images, encouraging others to report images depicting minors on Reddit and model-hosting sites.



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