ChatGPT's beta launch exceeded 1 million users in less than a week, attracting the attention of almost everyone in the entire tech ecosystem. I read articles about it in the New York Times, the Financial Times and The Atlantic, three top media sources in my books. The AI garners work-place buzz under the possibility that its generation is so effective, it might pose a threat to human jobs such as copywriting, answering customer service inquiries, writing news reports, and creating legal documents. Large Language Models (LLMs), and generative AI like ChatGPT to the workplace--especially where the reliability of information is paramount. I met with the executive team at Hebbia AI, a startup leading research efforts on LLMs, to dig in.

This is the future of search. The online interface can provide instant answers to any query using natural language processing and machine learning technologies like OpenAI Codex to translate natural language into SQL. This allows anyone to navigate large data sets like Twitter.

While recent work on text-conditional 3D object generation has shown promising results, the state-of-the-art methods typically require multiple GPU-hours to produce a single sample. This is in stark contrast to state-of-the-art generative image models, which produce samples in a number of seconds or minutes. In this paper, we explore an alternative method for 3D object generation which produces 3D models in only 1-2 minutes on a single GPU. Our method first generates a single synthetic view using a text-to-image diffusion model, and then produces a 3D point cloud using a second diffusion model which conditions on the generated image. While our method still falls short of the state-of-the-art in terms of sample quality, it is one to two orders of magnitude faster to sample from, offering a practical trade-off for some use cases. We release our pre-trained point cloud diffusion models, as well as evaluation code and models, at https://github.com/openai/point-e.

Dec 15 (Reuters) - ChatGPT, the new chatbot that is the talk of Silicon Valley, can spit out haikus, crack jokes in Italian and may soon be the scourge of teachers everywhere facing fake essays generated by the AI-powered technology. But a question it can't fully answer is this: How will OpenAI make money? The research organization, co-founded by Elon Musk and investor Sam Altman and backed by $1 billion in funding from Microsoft Corp (MSFT.O), is expecting its business to surge. Three sources briefed on OpenAI's recent pitch to investors said the organization expects $200 million in revenue next year and $1 billion by 2024. The forecast, first reported by Reuters, represents how some in Silicon Valley are betting the underlying technology will go far beyond splashy and sometimes flawed public demos.

It will disappoint fans of The Terminator, but the AI revolution is coming not in the form of killer robots or dystopian autocracies, but chat bots. We were told it would mean the apocalypse. So far it looks a lot like customer service, albeit much better than usual. The latest revolution in public-facing artificial intelligence is ChatGPT, a piece of software designed by OpenAI, a California-based research company. GPT is short for Generative Pre-trained Transformer.

For the last few weeks, GPT-3, ChatGPT, and InstructGPT have taken the internet by storm. The large-language models (LLM) and transformer language models (TLM) have made great progress in "creating" AI-generated codes (OpenAI Codex), AI-generated texts (OpenAI GPT, ChatGPT, InstructGPT), AI-generated images (OpenAI DALL-E), and even AI-generated AI models (Not yet! These models have been generating human-like outputs that are indistinguishable from real human output. GPT (or any other LLM) can be used to create human-like bots on social networks. These bots can be tuned to generate biased texts that can elicit expected responses from real humans.

Writers, designers, and artists are not exactly enamoured by the rapid developments in AI'creativity'. Within the space of a couple of years, AI-powered generators have evolved from complex research tools into free-for-all search engines of the unknown. Image by DALL·E, prompt: 'Wallpaper* Magazine Technology' AI is effectively a mirror, sifting through the vast database of human creativity and cannily blending a bit of this and that in order to return a visual representation approaching or transcending that which we'd imagined, or maybe a chunk of text that hopefully organises a coherent set of thoughts. It comes with inbuilt biases gleaned from the source material and still suffers the occasional baffling but telling lapse of judgement or coherence. Image by DALL·E, prompt: 'Wallpaper* Magazine' It took about ten seconds for ChatGPT to turn a 14-word prompt ('Write an article about artificial intelligence and imagery in the style of Wallpaper* magazine') into a 300-word'article', coherent and credible enough to pass muster for anyone skimming the site for a primer on the topic or a bit of background.

OpenAI has ruined my favorite assignment from when I was (briefly) a high school English teacher: Come up with a two-sentence horror story. All you really need to do the assignment is a topic and an idea of what's frightening. It seems so… human and creative, and yet, OpenAI does it better than most of my high school students ever did. What does OpenAI, which launched ChatGPT to much fanfare last week, offer developers? I fell down a rabbit hole exploring the private artificial intelligence company's playground options.

This year, we've seen the introduction of powerful generative AI systems that have the ability to create images and text on demand. At the same time, regulators are on the move. Europe is in the middle of finalizing its AI regulation (the AI Act), which aims to put strict rules on high-risk AI systems. Canada, the UK, the US, and China have all introduced their own approaches to regulating high-impact AI. But general-purpose AI seems to be an afterthought rather than the core focus.

OpenAI co-founder Sam Altman warns against using ChatGPT for important topics. Even faster and more intense than image generators, AI technology has reached the mainstream through ChatGPT. On Twitter, #ChatGPT is trending, and countless small and large media are reporting on the sometimes startling answers and texts of OpenAI's latest text model. The enormous response proves above all: training with human feedback works. The fact that ChatGPT is so well received probably has less to do with the output text or code, which is qualitatively on par with what GPT-3.5 has been producing since early 2022 and GPT-3 since 2020.