ChatGPT, Lensa, Stable Diffusion, and DALL-E: Generative AI, explained

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They are not designed to be compliant with General Data Protection Regulation (GDPR) and other copyright laws, so it’s imperative to pay close attention to your enterprises’ uses of the platforms. For businesses, efficiency is arguably the most compelling benefit of generative AI because it can enable enterprises to automate specific tasks and focus their time, energy and resources on more important strategic objectives. This can result in lower labor costs, greater operational efficiency and new insights into how well certain business processes are — or are not — performing.

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If implementing AI is too cumbersome an endeavor, then it defeats the purpose of increasing a company’s productivity. For executives and boards to agree to invest in generative AI, they’ll need a clear Yakov Livshits plan on how your organization will make training and adoption as seamless as possible. You’ll get quick answers to complex questions,  along with more detailed breakdowns for further context.

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A 2022 McKinsey survey shows that AI adoption has more than doubled over the past five years, and investment in AI is increasing apace. It’s clear that generative AI tools like ChatGPT and DALL-E (a tool for AI-generated art) have the potential to change how a range of jobs are performed. The full scope Yakov Livshits of that impact, though, is still unknown—as are the risks. Falsified information can make it easier to impersonate people for cyber attacks. It operates on AI models and algorithms that are trained on large unlabeled data sets, which require complex math and lots of computing power to create.

generative ai explained

By automating the music creation process, generative AI allows artists and content creators to focus on other aspects of their projects. Machine learning is the ability to train computer software to make predictions based on data. “When you think about an organization like ours, we have 360,000 people, we have lots of tools and capabilities built in the more than 100 years of our history,” he said at the time. AI Ethics and AI Law also stridently enter into the prompt engineering domain. Generative AI is a disruptive technology that can generate artifacts that previously relied on humans, delivering innovative results without the biases of human experiences and thought processes. In the same way, decisions we make about AI now could have ripple effects.

What kinds of problems can a generative AI model solve?

For example, such breakthrough technologies as GANs and transformer-based algorithms. The more neural networks intrude on our lives, the more the areas of discriminative and generative modeling grow. Jokes aside, generative AI allows computers Yakov Livshits to abstract the underlying patterns related to the input data so that the model can generate or output new content. The interesting thing is, it isn’t a painting drawn by some famous artist, nor is it a photo taken by a satellite.

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.

This has given organizations the ability to more easily and quickly leverage a large amount of unlabeled data to create foundation models. As the name suggests, foundation models can be used as a base for AI systems that can perform multiple tasks. The explosive growth of generative AI shows no sign of abating, and as more businesses embrace digitization and automation, generative AI looks set to play a central role in the future of industry. The capabilities of generative AI have already proven valuable in areas such as content creation, software development and medicine, and as the technology continues to evolve, its applications and use cases expand.

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Another consideration to always keep in your presence of mind is that sometimes a generative AI app will devise a response that is aimed at appeasing you. It is merely as a result of the data training on zillions of writing compositions from the Internet that the generative AI was data-trained on, see my detailed explanation at the link here. You can anticipate that AI researchers will continue to examine what works and what doesn’t work when it comes to ToT. We will ask generative AI a question or try to get it to solve a problem.

  • I show several sample prompts to encourage you to consider how you might want to formulate your own favored prompt to invoke the Tree of Thoughts when using conventional generative AI.
  • Everything in the infographic above – from illustrations and icons to the text descriptions⁠—was created using generative AI tools such as Midjourney.
  • It can also be used in content creation, personalization, and innovation.
  • 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.

As noted in the above excerpt, an add-on to generative AI that consists of several modules was devised and then tested using a problem-solving setting involving figuring out Sudoku puzzles. The researchers provided results that once again suggest the Tree of Thoughts technique and technology can be beneficial. First, if you are paying for the use of your generative AI app, there is a possibility that trying to use a Tree of Thoughts technique or technology might incur added costs. The same applies generally to doing any advanced prompting techniques such as Chain of Thought, Skeleton of Thought (see my coverage at the link here), multi-personas, mega-personas, etc. It is conceivable that the generative AI will undertake more computational activity to undertake those techniques.

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You’ve probably seen that generative AI tools (toys?) like ChatGPT can generate endless hours of entertainment. Generative AI tools can produce a wide variety of credible writing in seconds, then respond to criticism to make the writing more fit for purpose. This has implications for a wide variety of industries, from IT and software organizations that can benefit from the instantaneous, largely correct code generated by AI models to organizations in need of marketing copy. In short, any organization that needs to produce clear written materials potentially stands to benefit. Organizations can also use generative AI to create more technical materials, such as higher-resolution versions of medical images. And with the time and resources saved here, organizations can pursue new business opportunities and the chance to create more value.

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