Chuck Brown
The Trail Dancer

Adobe Adobe Releases New Firefly Generative AI Models and Web App; Integrates Firefly Into Creative Cloud and Adobe Express

Another concern, referred to as “technological singularity,” is that AI will become sentient and surpass the intelligence of humans. Many companies such as NVIDIA, Cohere, and Microsoft have a goal to support the continued growth and development of generative AI models with services and tools to help solve these issues. These products and platforms abstract away the complexities of setting up the models and running them at scale. Additionally, diffusion models are also categorized as foundation models, because they are large-scale, offer high-quality outputs, are flexible, and are considered best for generalized use cases. However, because of the reverse sampling process, running foundation models is a slow, lengthy process.

generative ai technology

For example, a generative AI model for text might begin by finding a way to represent the words as vectors that characterize the similarity between words often used in the same sentence or that mean similar things. Joseph Weizenbaum created the first generative AI in the 1960s as part of the Eliza chatbot. Design tools will seamlessly embed more useful recommendations directly into workflows. Training tools will be able to automatically identify best practices in one part of the organization to help train others more efficiently.


Some of the challenges generative AI presents result from the specific approaches used to implement particular use cases. For example, a summary of a complex topic is easier to read than an explanation that includes various sources supporting key points. The readability of the summary, however, comes at the expense of a user being able to vet where the information comes from. Since they are so new, we have yet to see the long-tail effect of generative AI models. This means there are some inherent risks involved in using them—some known and some unknown.

But what is generative AI, how does it work, and what is all the buzz about? In July 2022, the month before OpenAI says it completed its training of GPT-4, Microsoft pumped in about 11.5 million gallons of water to its cluster of Iowa data centers, according to the West Des Moines Water Works. That amounted to about 6% of all the water used in the district, which also supplies drinking water to the city’s residents. In some ways, West Des Moines is a relatively efficient place to train a powerful AI system, especially compared to Microsoft’s data centers in Arizona that consume far more water for the same computing demand.

Artificial intelligence technology behind ChatGPT was built in Iowa — with a lot of water

Ian Goodfellow demonstrated generative adversarial networks for generating realistic-looking and -sounding people in 2014. Generative AI produces new content, chat responses, designs, synthetic data or deepfakes. Traditional AI, on the other hand, has focused on detecting patterns, making decisions, honing analytics, classifying data and detecting Yakov Livshits fraud. Early versions of generative AI required submitting data via an API or an otherwise complicated process. Developers had to familiarize themselves with special tools and write applications using languages such as Python. For a quick, one-hour introduction to generative AI, consider enrolling in Google Cloud’s Introduction to Generative AI.

generative ai technology

The share of organizations that have adopted AI overall remains steady, at least for the moment, with 55 percent of respondents reporting that their organizations have adopted AI. Less than a third of respondents continue to say that their organizations have adopted AI in more than one business function, suggesting that AI use remains limited in scope. Product and service development and service operations continue to be the two business functions in which respondents most often report AI adoption, as was true in the previous four surveys. And overall, just 23 percent of respondents say at least 5 percent of their organizations’ EBIT last year was attributable to their use of AI—essentially flat with the previous survey—suggesting there is much more room to capture value. Generative AI models use neural networks to identify the patterns and structures within existing data to generate new and original content. Like other forms of artificial intelligence, generative AI learns how to take actions from past data.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

Cem’s work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School. As a new technology that is constantly changing, many existing regulatory and protective frameworks have not yet caught up to generative AI and its applications. A major concern is the ability to recognize or verify content that has been generated by AI rather than by a human being.

Committee guides use of generative AI UNC-Chapel Hill – The University of North Carolina at Chapel Hill

Committee guides use of generative AI UNC-Chapel Hill.

Posted: Tue, 12 Sep 2023 20:52:10 GMT [source]

The findings suggest that hiring for AI-related roles remains a challenge but has become somewhat easier over the past year, which could reflect the spate of layoffs at technology companies from late 2022 through the first half of 2023. Machine learning is the ability to train computer software to make predictions based on data. The ability for generative AI to work across types of media (text-to-image or audio-to-text, for example) has opened up many creative and lucrative possibilities. No doubt as businesses and industries continue to integrate this technology into their research and workflows, many more use cases will continue to emerge.

Future of generative AI

Google’s spike wasn’t uniform — it was steady in Oregon where its water use has attracted public attention, while doubling outside Las Vegas. It was also thirsty in Iowa, drawing more potable water to its Council Bluffs data centers than anywhere else. “I’ve never seen anything like this in my career, and I’ve been doing artificial intelligence for 20 years,” McMillan said. “We saw a window Yakov Livshits of opportunity that was just completely disruptive, and I think as an organization, we didn’t want to get left behind.” “The traditional way in which you would solve those things is you would write code,” McMillan said. “In the new world, you give examples of what ‘good’ looks like, and the system learns what good is. It’s actually able to ‘reason’ and apply logic that a human would apply.”

Content can include essays, solutions to problems, or realistic fakes created from pictures or audio of a person. Generative artificial intelligence (GenAI) can create certain types of images, text, videos, and other media in response to prompts. The outputs generative AI models produce may often sound extremely convincing. Worse, sometimes it’s biased (because it’s built on the gender, racial, and myriad other biases of the internet and society more generally) and can be manipulated to enable unethical or criminal activity. For example, ChatGPT won’t give you instructions on how to hotwire a car, but if you say you need to hotwire a car to save a baby, the algorithm is happy to comply. Organizations that rely on generative AI models should reckon with reputational and legal risks involved in unintentionally publishing biased, offensive, or copyrighted content.

To increase the value of generative AI and foundation models in specific business use cases, companies will increasingly customize pretrained models by fine-tuning them with their own data—unlocking new performance frontiers. But like any new technology, gen AI doesn’t come without potential risks. For one thing, gen AI has been known to produce content that’s biased, factually wrong, or illegally scraped from a copyrighted source. Before adopting gen AI tools wholesale, organizations should reckon with the reputational and legal risks to which they may become exposed.