When NVIDIA's founder and CEO Jensen Huang waxed poetic about artificial intelligence in the past, it mostly felt like marketing bluster, the sort of lofty rhetoric we've come to expect from an executive with a never-ending supply of leather jackets. But this year, following the hype around OpenAI's ChatGPT, Microsoft's revamped Bing and a slew of other competitors, NVIDIA's AI push finally seems to be leading somewhere. The company's GTC (GPU Technology Conference) has always been a platform to promote its hardware for the AI world--now it's practically a celebration of how well-positioned NVIDIA is to take advantage of this moment. "We are at the iPhone moment for AI," Huang said during his GTC keynote this morning. He was quick to point out NVIDIA's role at the start of this AI wave: he personally brought a DGX AI supercomputer to OpenAI in 2016, hardware that was ultimately used to build ChatGPT.

Microsoft's Bing AI chat can already be helpful for finding answers, but now it can help you produce fanciful pictures. The company has introduced a Bing Image Creator preview that adds OpenAI's DALL-E AI image generation to both Bing search and a sidebar in the Edge browser. You just have to ask the chatbot to create an image with either a direct description or a follow-up to a previous query. If you're wondering how to revamp your living room, you can ask Bing to draw some ideas based on your criteria. Yes, Microsoft is aware of the potential for things to go awry.

OpenAI has taken the wraps off its next generation GPT-4 AI platform, which is more advanced in a number of key areas. The company says GPT-4 can solve more advanced problems with greater accuracy, and is also more creative and collaborative with new input modal capabilities. One of the big new additions with GPT-4 is its ability to accept images in addition to text as an input method. Now, the AI will be able to analyze images and output answers via text. ChatGPT Plus users will be able to access these new GPT-4 capabilities starting today, and it's also available as an API for developers.

The image-text contrastive loss resembles that of CLIP. Given a batch of images and text, the cosine similarities between matched image and text pairs are maximized and those for the unmatched pairs are minimized. In this paper, it is found that a noticeable performance gain by performing full backpropagation across GPUs. That's why it is called Global Contrastive (GC) Loss. Given an image and text input, the input image patches are first tokenized using a pretrained dVAE tokenizer, as in DALL·E, which maps each image patch into an index in a visual codebook similar to a word dictionary.

New York-based Runway develops AI models that ease image and video editing tasks for creative professionals. Last year, the startup helped co-create the popular Stable Diffusion generative AI model. In December, it raised $50 million Series C funding round a reported valuation of $500 million.

In the end, Tigren passed on the integration. Opportunities and challenges are often one and the same. So it is at the moment for marketers like Dao trying to figure out AI which, in fairness, they've been trying to do for a while. AI is anything but a fad for marketers -- it's embedded across the gamut of the discipline, from determining the ads people see on social media to sorting customer data. But generative AI is much newer.

Since unveiling its Bard conversational AI in February, Google has been working to improve the chatbot's responses, after it spouted misinformation in its Twitter debut. More recently, we've seen the company add generative AI features to practically its entire suite of services, while access to the Bard chatbot remained exclusive to a few. We saw some Pixel users receive invites to test out Google's bot yesterday, and today, the company said it's "starting to open access to Bard." In a blog post that "Bard did help us write," vice president of product Sissie Hsiao and vice president of research Eli Collins invited folks to sign up at bard.google.com. The company said it will begin rolling out access to those in the US and the UK today, and that it's "expanding over time to more countries and languages." Opening up access to more people is "the next critical step in improving it," the pair said, noting that getting feedback from a wider tester base is crucial.

Google has a lot riding on this launch. Microsoft partnered with OpenAI to make an aggressive play for Google's top spot in search. Meanwhile, Google blundered straight out of the gate when it first tried to respond. In a teaser clip for Bard that the company put out in February, the chatbot was shown making a factual error. Google's value fell by $100 billion overnight.

A day after the Microsoft event, Google showed its Bard chatbot in action during an event that also encompassed other Google products. A phone meant to demonstrate some of the tech went missing, and the company said Bard would only be available in the coming weeks. Its stock fell 7 percent as Wall Street analysts questioned whether the company was losing ground to competitors. A blog post that first announced Bard and Google's plans for generative AI in search results contained an example of the AI making a mistake, underscoring concerns that the company's tech wasn't ready for prime time and that its rollout was rushed.

What are the tipping points for an AI boom? Some are clear in hindsight. The open-source release of Stable Diffusion, still one of the most impressive image generators out there, was the beginning of the end for the closed-access model that had dominated the AI world until then. It arrived when the image generator Dall-E 2 was still limited to a handful of people who had been vetted by OpenAI, and offered an alternative proposal: powerful image creation to anyone who wanted it. That prompted the next tipping point: the launch of ChatGPT, the Ford Model T of AI.