AI chatbot experts are all talking about -- and talking to -- a newish research project from artificial intelligence research organization OpenAI. Conceptually, ChatGPT can be used like the AI art tools in the sense that minimal text input by the user produces credible synthetic media -- paragraphs instead of images. In fact, it can write convincing, often compelling essays, stories and even poems. And, like the AI image creators, you can direct ChatGPT to write prose in specific styles. I told ChatGPT to tell me about Twitter in three separate queries: one in the style of Ernest Hemingway, another in the style of Mark Twain and the third in the form of a limerick.

Did a human write that, or ChatGPT? It can be hard to tell -- perhaps too hard, its creator OpenAI thinks, which is why it is working on a way to "watermark" AI-generated content. In a lecture at the University of Austin, computer science professor Scott Aaronson, currently a guest researcher at OpenAI, revealed that OpenAI is developing a tool for "statistically watermarking the outputs of a text [AI system]." Whenever a system -- say, ChatGPT -- generates text, the tool would embed an "unnoticeable secret signal" indicating where the text came from. OpenAI engineer Hendrik Kirchner built a working prototype, Aaronson says, and the hope is to build it into future OpenAI-developed systems.

SmartClick builds deep tech innovations based on artificial intelligence & machine learning. As traditional methods of reaching a mass audience dry up or become too competitive, it gets challenging to find and nurture the audience who are more likely to transmit your content and take action. With the rise of the internet, the media landscape has changed significantly, paving the way for millions of content creators who have shaped the creator economy space. And, like with any trend that gets popular quickly, the creator economy is revolutionizing marketing and business strategies as more brands now rely on trusted online personalities to become advocates who spread their brand message. The creator economy skyrocketed even further with the rapid growth of artificial intelligence technology that has amplified the industry's possibilities making it easier for creators to produce better content.

The OpenAI Startup Fund is investing $100 million to help AI companies have a profound, positive impact on the world. We're looking to partner with a small number of early-stage startups in fields where artificial intelligence can have a transformative effect--like health care, climate change, and education--and where AI tools can empower people by helping them be more productive. The fund is managed by a dedicated team with expertise in investing, ML, engineering, talent and operations, including members of OpenAI leadership and technical staff. The fund's investors consist of Microsoft and other OpenAI partners. In addition to capital, companies in the OpenAI Startup Fund will get early access to future OpenAI systems, support from the fund's team and credits on Azure.

As the effects of climate change become more apparent, there is an urgent need to find solutions that can help to reduce greenhouse gas emissions and slow the pace of global warming. One technology that is gaining attention in this effort is machine learning, which has the potential to help us understand and address some of the most pressing challenges facing our planet. One of the key ways that machine learning can help in the fight against climate change is by providing us with insights and predictions that can inform decision making and policy. For example, machine learning algorithms can be used to analyze data on global temperatures, atmospheric carbon dioxide levels, and other environmental indicators, providing us with a better understanding of the current state of the planet and the likely impacts of different actions. Machine learning can also be used to optimize processes and systems in ways that reduce greenhouse gas emissions.

Let's begin with the objective part of the story. This section is slightly technical (although not difficult), so feel free to skim through it (still worth reading if you plan to use the model). Stable Diffusion 2 is the generic name of an entire family of models that stem from a common baseline: Stable Diffusion 2.0-base (SD 2.0-base) a raw text-to-image model. The baseline model is trained on an aesthetic subset of the open dataset LAION-5B (keep this in mind, it will be important later) and generates 512x512 images. On top of SD 2.0-base, Stability.ai

Check out all the on-demand sessions from the Intelligent Security Summit here. Gartner recently released its list of 7 Technology Disruptions That Will Impact Sales Through 2027. One was generative Artificial Intelligence. Gartner defined generative AI as AI that "learns from existing content artifacts to generate new, realistic artifacts that reflect the characteristics of the training data, but do not repeat it." In simple terms, it can produce entirely new content, like images, videos, text and code, with very simple inputs.

Those who, like this columnist, spend too much time online will have noticed a kind of feeding frenzy over the past two weeks. The cause has been the release of an interesting chatbot – a software application capable of conducting an online conversation. The particular bot creating the fuss is ChatGPT, a prototype artificial intelligence (AI) chatbot that focuses on usability and dialogue and was developed by OpenAI, an AI research laboratory based in San Francisco. ChatGPT uses a large language model built via machine-learning methods and is based on OpenAI's GPT-3 model, which is capable of producing human-like text when given a prompt in natural language. It's an example of what has come to be called "generative AI": software that uses machine-learning algorithms to enable machines to generate artificial content – text, images, audio and video content based on its training data – in a way that might persuade a human user into believing that its outputs are "real".

Artificial intelligence software programs are becoming shockingly adept at carrying on conversations, winning board games and generating artwork -- but what about creating software programs? In a newly published paper, researchers at Google DeepMind say their AlphaCode program can keep up with the average human coder in standardized programming contests. "This result marks the first time an artificial intelligence system has performed competitively in programming contests," the researchers report in this week's issue of the journal Science. There's no need to sound the alarm about Skynet just yet: DeepMind's code-generating system earned an average ranking in the top 54.3% in simulated evaluations on recent programming competitions on the Codeforces platform -- which is a very "average" average. "Competitive programming is an extremely difficult challenge, and there's a massive gap between where we are now (solving around 30% of problems in 10 submissions) and top programmers (solving 90% of problems in a single submission)," DeepMind research scientist Yujia Li, one of the Science paper's principal authors, told GeekWire in an email.

Something incredible is happening in AI right now, and it's not entirely to the good. Everybody is talking about systems like chatGPT (OpenAI), Dall-E 2, and Lensa that generate text and images that look remarkably human-like, with astonishingly little effort. These systems can be incredibly fun to play with. Take this example, generated by chatGPT by Henry Minsky (son of Marvin Minsky, one of AI's founders), who asked chatGPT to "Describe losing your sock in the dryer in the style of the declaration of independence": When in the course of household events, it becomes necessary for one to dissolve the bonds that have connected a sock to its mate, and to assume among the powers of the laundry room, the separate and equal station to which the laws of physics and of household maintenance entitle it, a decent respect to the opinions of socks requires that it should declare the causes which impel it to go missing. We hold these truths to be self-evident, that all socks are created equal, and are endowed by their manufacturer with certain unalienable rights….