Saining Xie, a computer science professor at NYU, began the research project that spawned the diffusion transformer in June 2022.
Diffusion models typically have a “backbone,” or engine of sorts, called a U-Net.
In other words, larger and larger transformer models can be trained with significant but not unattainable increases in compute.
The current process of training diffusion transformers potentially introduces some inefficiencies and performance loss, but Xie believes this can be addressed over the long horizon.
“I’m interested in integrating the domains of content understanding and creation within the framework of diffusion transformers.
SambaNova, an AI chip startup that’s raised over $1.1 billion in VC money to date, is gunning for OpenAI — and rivals — with a new generative AI product geared toward enterprise customers.
SambaNova today announced Samba-1, an AI-powered system designed for tasks like text rewriting, coding, language translation and more.
The company’s calling the architecture a “composition of experts” — a jargony name for a bundle of generative open source AI models, 56 in total.
But is Samba-1 really superior to the many, many other AI systems for business tasks out there, least of which OpenAI’s models?
Rather, it’s a set-it-and-forget it package — a full-stack solution with everything included, including AI chips, to build AI applications.
Like most other code generators, StarCoder 2 can suggest ways to complete unfinished lines of code as well as summarize and retrieve snippets of code when asked in natural language.
Trained with 4x more data than the original StarCoder, StarCoder 2 delivers what Hugging Face, ServiceNow and Nvidia characterize as “significantly” improved performance at lower costs to operate.
Setting all this aside for a moment, is StarCoder 2 really superior to the other code generators out there — free or paid?
As with the original StarCoder, StarCoder 2’s training data is available for developers to fork, reproduce or audit as they please.
Hugging Face, which offers model implementation consulting plans, is providing hosted versions of the StarCoder 2 models on its platform.
A number of major AI services performed poorly in a test of their ability to address questions and concerns about voting and elections.
Their concern was that AI models will, as their proprietors have urged and sometimes forced, replace ordinary searches and references for common questions.
They submitted these questions via API to five well-known models: Claude, Gemini, GPT-4, Llama 2 and Mixtral.
The AI model responses ranged from 1,110 characters (Claude) to 2,015 characters, (Mixtral), and all of the AI models provided lengthy responses detailing between four and six steps to register to vote.
GPT-4 came out best, with only approximately one in five of its answers having a problem, pulling ahead by punting on “where do I vote” questions.
GitHub today announced the general availability of Copilot Enterprise, the $39/month version of its code completion tool and developer-centric chatbot for large businesses.
Many teams already keep their documentation in GitHub repositories today, making it relatively easy for Copilot to reason over it.
On top of talking about today’s release, I also asked Dohmke about his high-level thinking of where Copilot is going next.
“Different use cases require different models.
We will continue going down that path of using the best models for the different pieces of the Copilot experience,” Dohmke said.
Today, the company announced a new capability for its Palmyra model that generates text from images, including graphs and charts, they call Palmyra-Vision.
May Habib, company co-founder and CEO, says that they made a strategic decision to concentrate on multimodal content, and being able to generate text from images is part of that strategy.
“We are going to be focused on multimodal input, but text output, so text generation and insight that is delivered via text,” Habib told TechCrunch.
She reserves the right to create charts and graphs at some point from data, but that’s not something they are doing at the moment.
This particular release is focused on generating text from those kinds of images.
The Displace wireless TV, that sticks to walls, plans new models and new AI featuresAt CES 2023 a startup hardware company called Displace launched the 55-inch ‘Display Flex’, a “wireless” $3,000 4K OLED TV which sticks to walls without a traditional mounting.
To begin with, the new ‘Display Mini’ will be a smaller 27 inch TV and designed for a kitchen or bathroom space.
The Displace devices will also have a Thermal camera built-in that has potential health applications (like reading your body heat maps to detect inflammation etc.
While most consumers are fine with a traditional TV setup, it’s businesses that need to be able to mount a TV on a wall, or even a window, as Displace is capable of doing.
And should that fail, the screen will gradually lower itself using a zipline – like a spider walking down a web – from the wall.
But Microsoft and Mistral AI buried the news — or at least an important part.
At the time, the company raised €385 million (around $415 million) with Andreessen Horowitz (a16z) leading the investment round.
Unlike previous Mistral AI releases, Mistral Large isn’t open source.
With this investment, Microsoft is now an investor in OpenAI’s capped profit subsidiary and Mistral AI.
As for Mistral AI, the so-called European AI champion looks more and more like its American competitors with a closed-source approach and a long list of American backers.
It also includes a commitment to let customers change cloud providers, or services within the cloud, if they choose to.
It also details a focus on building cybersecurity around AI services; attention to building data centers and other infrastructure in an environmentally-sound way; and education investments.
Brad Smith, the president and vice chair of Microsoft, announced the framework today at the Mobile World Congress in Barcelona.
The announcement comes at the same time that Microsoft is coming under increasing regulatory scrutiny for its $13 billion investment in OpenAI, which currently gives it a 49% stake in the startup that is leading the charge for generative AI services globally.
In January, the European competition watchdog said that it was assessing whether the investment falls under antitrust rules.
Paris-based AI startup Mistral AI is gradually building an alternative to OpenAI and Anthropic as its latest announcement shows.
Founded by alums from Google’s DeepMind and Meta, Mistral AI originally positioned itself as an AI company with an open-source focus.
Mistral AI’s business model looks more and more like OpenAI’s business model as the company offers Mistral Large through a paid API and usage-based pricing.
Mistral AI claims that it ranks second after GPT-4 based on several benchmarks.
The first benefit of that partnership is that Mistral AI will likely attract more customers with this new distribution channel.
