Category: Scoop.it

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The AI Sommelier: AI Has Revolutionized the Wine Industry and How Your Industry Benefit

The integration of Artificial Intelligence (AI) in the wine industry marks a significant shift from traditional viticulture and enology practices to a more technologically advanced approach. AI’s application ranges from vineyard management to winemaking processes, ultimately impacting the quality, efficiency, and sustainability of wine production.

Read the full article at: www.forbes.com

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Google Reveals Gemini, Its Much-Anticipated Large Language Model

Google’s Gemini is available to consumers in Bard or Pixel 8 Pro now, with an enterprise model coming Dec. 13. Get more details about the LLM.

Gemini is available to consumers in Bard or Pixel 8 Pro now, with an enterprise model coming Dec. 13.

Google has revealed Gemini, its long-rumored large language model and rival to GPT-4. Global users of Google Bard and the Pixel 8 Pro will be able to run Gemini starting now; an enterprise product, Gemini Pro, is coming on Dec. 13. Developers can sign up now for an early preview in Android AICore.

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What is Gemini?

Gemini is a large language model that runs generative artificial intelligence applications; it can summarize text, create images and answer questions. Gemini was trained on Google’s Tensor Processing Units v4 and v5e.

Google’s Bard is a generative AI based on the PaLM large language mode. Starting today, Gemini will be used to give Bard “more advanced reasoning, planning, understanding and more,” according to a Google press release.

SEE: Microsoft invested $3.2 billion on AI in the UK. (TechRepublic) 

Gemini size options

Gemini comes in three model sizes: Ultra, Pro and Nano. Ultra is the most capable, Nano is the smallest and most efficient, and Pro sits in the middle for general tasks. The Nano version is what Google is using on the Pixel, while Bard gets Pro. Google says it plans to run “extensive trust and safety checks” before releasing Gemini Ultra to select groups.

Gemini for coding

Gemini can code in Python, Java, C++, Go and other popular programming languages. Google used Gemini to upgrade Google’s AI-powered code generation system, AlphaCode.

Gemini will be added to more Google products

Next, Google plans to bring Gemini to Ads, Chrome and Duet AI. In the future, Gemini will be used in Google Search as well.

Competitors to Gemini

Gemini and the products built with it, such as chatbots, will compete with OpenAI’s GPT-4, Microsoft’s Copilot (which is based on OpenAI’s GPT-4), Anthropic’s Claude AI, Meta’s Llama 2 and more. Google claims Gemini Ultra outperforms GPT-4 in several benchmarks, including the massive multitask language understanding general knowledge test and in Python code generation.

Does Gemini have an enterprise product?

Starting Dec. 13, enterprise customers and developers will be able to access Gemini Pro through the Gemini API in Google’s Vertex AI or Google AI Studio.

Google expects Gemini Nano to be generally available for developers and enterprise customers in early 2024. Android developers can use this LLM to build Gemini apps on-device through AndroidAICore.

Possible enterprise use cases for Gemini

More must-read AI coverage

Of particular interest to enterprise use cases might be Gemini’s ability to “understand and reason about users’ intent,” said Palash Nandy, engineering director at Google, in a demonstration video. Gemini generates a bespoke UI depending on whether the user is looking for images or text. In the same UI, Gemini will flag areas in which it doesn’t have enough information and ask for clarification. Through the bespoke UI, the user can explore other options with increasing detail.

Gemini has been trained on multimodal content from the very beginning instead of starting with text and expanding to audio, images and video later, letting Gemini parse written or visual information with equal acuity. One example of how this might be useful for business Google provides is the prompt “Could Gemini help make a demo based on this video?” in which the AI translates video content to an original animation.

Gemini’s timing compared to other popular LLMs

Gemini has been hotly rumored, as Google tries to compete with OpenAI. The New York Times reported Google executives were “shaken” by OpenAI’s tech in January 2023. More recently, Google supposedly struggled with releasing Gemini in languages other than English, leading to a delay of an in-person launch event.

However, releasing Google’s own large language model after ChatGPT has received gradual GPT-4 powered updates for nearly a year means Google has the advantage of leapfrogging the last year of AI development. For example, Gemini is multimodal (i.e., able to work with text, video, speech and code) and lives natively on the Google Pixel 8. Users can access Gemini on their Google Pixel 8 without an internet connection, unlike ChatGPT, which started out in a browser.

Read the full article at: www.techrepublic.com

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Is AI Mimicking Consciousness or Truly Becoming Aware Gradually?

 

AI’s remarkable abilities, like those seen in ChatGPT, often seem conscious due to their human-like interactions.

 

The question is whether the language model also perceives our text when we prompt it. Or is it just a zombie, working based on clever pattern-matching algorithms? Based on the text it generates, it is easy to be swayed that the system might be conscious. However, in this new research, Jaan Aru, Matthew Larkum and Mac Shine take a neuroscientific angle to answer this question.

 

All three being neuroscientists, these authors argue that although the responses of systems like ChatGPT seem conscious, they are most likely not. First, the inputs to language models lack the embodied, embedded information content characteristic of our sensory contact with the world around us. Secondly, the architectures of present-day AI algorithms are missing key features of the thalamocortical system that have been linked to conscious awareness in mammals. Finally, the evolutionary and developmental trajectories that led to the emergence of living conscious organisms arguably have no parallels in artificial systems as envisioned today.

 

The existence of living organisms depends on their actions and their survival is intricately linked to multi-level cellular, inter-cellular, and organismal processes culminating in agency and consciousness. Thus, while it is tempting to assume that ChatGPT and similar systems might be conscious, this would severely underestimate the complexity of the neural mechanisms that generate consciousness in our brains.

 

Researchers do not have a consensus on how consciousness rises in our brains. What we know, and what this new paper points out, is that the mechanisms are likely way more complex than the mechanisms underlying current language models. For instance, as pointed out in this work, real neurons are not akin neurons in artificial neural networks. Biological neurons are real physical entities, which can grow and change shape, whereas neurons in large language models are just meaningless pieces of code. We still have a long way to understand consciousness and, hence, a long way to conscious machines.

Read the full article at: neurosciencenews.com

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