Explainer: What is Generative AI, the technology behind OpenAI’s ChatGPT?

For example, it can turn text inputs into an image, turn an image into a song, or turn video into text. Generative AI could also play a role in various aspects of data processing, transformation, labeling and vetting as part of augmented analytics workflows. Semantic web applications could use generative AI to automatically map internal taxonomies describing Yakov Livshits job skills to different taxonomies on skills training and recruitment sites. Similarly, business teams will use these models to transform and label third-party data for more sophisticated risk assessments and opportunity analysis capabilities. The recent progress in LLMs provides an ideal starting point for customizing applications for different use cases.

Each platform has its own benefits, downsides, and quirks, but all can turn plain text instructions into stunning images in just a few seconds. You have probably heard the term “generative AI” tossed around in tech circles or investment discussions. It’s one of those buzzwords that seems to be on everyone’s lips nowadays, starting when OpenAI released the ChatGPT tool in November 2022. But the name alone doesn’t really explain what’s going on, and there are many ways to look at this interesting toolkit.

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Generative AI has revolutionized the visual domain by enabling the generation of realistic images, videos, and visual effects. Generative adversarial networks (GANs) are widely used for visual generation tasks. Visual generation has applications in computer graphics, virtual reality, video game design, and even art generation. Thanks to its reliable and relatable nature, ChatGPT carved out a niche for many who work anywhere from customer support to content creation professions.

• Generative AI art models are trained on billions of images from across the internet.
• Encoder-decoder models, like Google’s Text-to-Text Transfer Transformer, or T5, combine features of both BERT and GPT-style models.
• Models can craft tunes and audio clips from text inputs, identify objects in videos while generating accompanying sounds, and even compose custom music.
• AI hallucinations can be false content, news, or information about people, events, or facts.

Needless to say, these technologies will provide substantial work for intellectual property attorneys in the coming years. In a six-week pilot at Deloitte with 55 developers for 6 weeks, a majority of users rated the resulting code’s accuracy at 65% or better, with a majority of the code coming from Codex. Overall, the Deloitte experiment found a 20% improvement in code development speed for relevant projects. Deloitte has also used Codex to translate code from one language to another.

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Managed services are a way to offload general tasks to an expert, in order to reduce costs, improve service quality, or free internal teams to do work that’s specific to your business. New services are experimenting with various generative AI techniques to create motion graphics. For example, Yakov Livshits some are able to match audio to a still image and make a subject’s mouth and facial expression appear to talk. In May, OpenAI CEO Sam Altman called for creating a new regulatory agency to oversee the development of artificial intelligence during a Congressional Hearing in Washington, DC.

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.

For one, software developers have increasingly been looking to generative AI tools like Tabnine, Magic AI and Github Copilot to not only ask specific coding-related questions, but also fix bugs and generate new code. And AI text generators are being used to simplify the writing process, whether it’s a blog, a song or a speech. “It’s essentially AI that can generate stuff,” Sarah Nagy, the CEO of Seek AI, a generative AI platform for data, told Built In. And, these days, some of the stuff generative AI produces is so good, it appears as if it were created by a human. Typically, it starts with a simple text input, called a prompt, in which the user describes the output they want.

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Ecrette Music – uses AI to create royalty free music for both personal and commercial projects. AIVA – uses AI algorithms to compose original music in various genres and styles. If you think back, when the graphing calculator emerged, how were teachers supposed to know whether their students did the math themselves?

But as an efficient way to perform calculations in parallel, GPUs have proven to be well suited for deep learning workloads. Starting with the input layer, which is composed of several nodes, data is introduced to the model and categorized accordingly before it’s moved forward to the next layer. The path that the data takes through each layer is based upon the calculations set in place for each node. Eventually, the data moves through each layer, picking up observations along the way that ultimately create the output, or final analysis, of the data.

Our professionals advise on the optimal deployment of this rapidly advancing technology and execute its implementation tailored to your preferences. Nevertheless, like any technological advancement, Yakov Livshits applying it requires many considerations. As this technology is embraced and refined, receiving an ongoing series of questions regarding its multifaceted implications is inevitable.