Amazon debuts generative AI tools that helps sellers write product descriptions
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Amazon debuts generative AI tools that helps sellers write product descriptions

Amazon debuts generative AI tools that helps sellers write product descriptions

What Is Generative AI? Definition, Applications, and Impact

Walmart’s approach to the technology is to employ large language models (LLMs) from technology providers rather than building its own. As LLMs continue to emerge, Walmart plans to harness multiple models, abstracting them through its own technology layer and offering access through tools such as My Assistant. Quidgest is a global technology company headquartered in Lisbon and a pioneer in intelligent software modeling and generation.

For example, you can “transfer” a piece of music from a classical to a jazz style. So, instead of paying attention to each word separately, the transformer attempts to identify the context that brings meaning to each word of the sequence. Transformer models use something called attention or self-attention mechanisms to detect subtle ways even distant data elements in a series influence and depend on each other. Both the encoder and the decoder in the transformer consist of multiple encoder blocks piled on top of one another. Each decoder receives the encoder layer outputs, derives context from them, and generates the output sequence. So, the adversarial nature of GANs lies in a game theoretic scenario in which the generator network must compete against the adversary.

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The odds are that we would program the app to do something akin to how humans seem to play chess. When considering what next move to make, the chess-playing program would examine a potential candidate for a move, such as moving the pawn, and consider the consequences that might arise. For those of you versed in Yakov Livshits the field of computer science, you undoubtedly have learned that a type of data structure known as a tree is commonly used to organize and search amongst data. The analogy to a nature-based tree is that the data structure has various branches or might have roots that extend from a base or key topic of interest.

No one has all the answers, but anticipating the questions is a great starting point. By taking the time to think about these questions and how they apply, you should be able to sound like an expert to your stakeholders and find the answers to these questions in the context of your own company. Notion is another example of an enterprise adding generative AI to their products. They’re offering generative AI features that give users the ability to turn meeting notes into summaries and generate next steps.

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But these techniques were limited to laboratories until the late 1970s, when scientists first developed computers powerful enough to mount them. Generative artificial intelligence (AI) is a type of AI that generates images, text, videos, and other media in response to inputted prompts. Generative AI has the potential to enhance human creativity in a variety of fields. By leveraging its ability to generate unique content based on learned patterns, generative AI can assist artists, writers, and designers in expanding their creative horizons. It can be used in music composition, video game design, advertising, and even healthcare.

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.

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As you may have noticed above, outputs from generative AI models can be indistinguishable from human-generated content, or they can seem a little uncanny. The results depend on the quality of the model—as we’ve seen, ChatGPT’s outputs so far appear superior to those of its predecessors—and the match between the model and the use case, or input. ChatGPT may be getting all the headlines now, but it’s not the first text-based machine learning model to make a splash. OpenAI’s GPT-3 and Google’s BERT both launched in recent years to some fanfare. But before ChatGPT, which by most accounts works pretty well most of the time (though it’s still being evaluated), AI chatbots didn’t always get the best reviews.

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Generative AI tools, like ChatGPT, Stable Diffusion, and DALL-E, are systems designed to produce something new based on its previous experience. Some of these can be accessed online for free or for a low-cost subscription. Rolling out new technology takes employees’ time away from other projects for training.

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 Yakov Livshits and running them at scale. The impact of generative models is wide-reaching, and its applications are only growing. Listed are just a few examples of how generative AI is helping to advance and transform the fields of transportation, natural sciences, and entertainment.

Generative AI models

The automaker’s intelligent G6 Coupe SUV, also powered by NVIDIA DRIVE Orin, will be made available to the European market next year. LeapMotor unveiled its new model, the C10 SUV, built on its LEAP 3.0 architecture. The vehicle is equipped with 30 high-resolution sensors, including lidar and 8-megapixel high-definition cameras, for accurate surround-perception capabilities. It’s powered by NVIDIA DRIVE Orin, which delivers 254 TOPS of compute to enable safe, high-speed and urban intelligent-driving capabilities. Such tools are part of the enterprise adoption boom, which also includes other retailers, such as Wayfair.

generative ai explained

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