Generative AI will really take off as it moves from playful to useful – VC Cafe

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Generative AI will indeed become magic as it moves from ‘playful’ to ‘useful’

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We will use many generative AI tools at work in the future, just like we use grammar and canned responses today…

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AI will become more vertical, and specific per role

— ez vidra (@ediggs) 5 November 2022
my prediction for 2023

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The generative AI hype cycle is at its peak. OpenAI, makers of the GPT-3 and Dall-e 2 among other AI innovations, is making its technology more widely available by opening an API (in beta) for businesses and developers to incorporate generative AI within their products. Is. In the announcement, OpenAI revealed last week that more than three million users now produce four million images every day using DLL-e. VC Cafe readers have seen my various posts on the potential of creative automation, the opportunities it brings, and the impact AI can have on jobs.

Currently, we are in the ‘agile’ phase of generative AI. People are trying things out and enjoying the ‘magic’ feeling of creating images, text and videos from a text prompt. However in practice the use cases are mostly limited to replacing stock photos with AI generated images. As an example I often use Del-E to create images to go with my blog posts. Microsoft went a step further by integrating Dell-E into the Office suite, allowing people to easily integrate AI generated images into their presentations.

According to Gartner’s “AI hype cycle”, generative AI is at the peak of inflated expectations (source)

We are starting to see more specialized models being trained for better use-case-specific results. But with Stable Diffusion, which already provides an open source generative AI API, we are starting to see developers train generative AI algorithms to perform specific tasks. For example, in the case of Israeli startup Strum, people pay $3 to train the system with their profile pictures to create cool portrait pictures with AI.

I believe the next step will be generative AI to perform specific tasks in the world of work. We already have a glimpse of this in text: Jasper.ai (which recently secured $125M in funding at a $1.5 billion valuation) and Copy.ai, already doing great work for marketing/ad copy are doing.

Startups are jumping at the opportunity. As APIs become more widely available, founders can focus on application layer generative AI, without the burden of developing their own models. Can startups model enterprise scale using open source technology or someone else’s API? There are many examples that prove that the answer is yes.

US and European Generative AI Landscape (source)

But what’s coming next? Can AI help us do our jobs better, no matter what you do? I’m not talking about replacing humans entirely, but actually enhancing performance, aiding in quality control, and enriching our frame of reference. I believe AI use cases will become more vertical and trained for specific tasks, each role in a company designed to help….

Forrester predicts that in 2023 10% of Fortune 500 companies will use AI to generate content. AI/ML Forrester analyst Rowan Curran said:

With the adoption of large language models so widely across a variety of use cases, the pace of AI change is happening so fast, that this prediction is already almost out of date.

I probably should have upvoted it. I think maybe 10% of Fortune 500 employees will use these tools as I modified it, because to me that speaks to the way this AI trend is evolving – I think it’s going to bubble up from the bottom as much. Coming from top to bottom.”

5 Ways Forrester Predicts AI Will Be “Indispensable” in 2023, VentureBeat

It’s not hard to imagine what this might look like using a simple idea building exercise:

Tech Jobs:

Developer + AI – coding autocomplete tools like Github’s Copilot or Israel’s Tabin, QA Designer + AI for AI – Text for 3D, Text to Image for Design, Automated Brand Asset Creation, etc. Product Manager + AI – GPT-3 for product specifications, recommendations for AI features, automated A/B testing Marketer + AI – GPT-3 for blog posts and ads, text to image business development + AI – text to video for product visualization, Speech to speech to localize messages in the local language, knowledge base for AI (eg pragma.ai) HR + AI – Video to text for onboarding and recruiting, GPT-3 personalized messaging for recruiters CFO + AI – AI for Book Keeping, Predictive Analytics for Revenue

Relative AI penetration by industry, from the Stanford AI Index 2022 Report (source)

And of course, non-technical jobs, ranging from oil and gas to automotive, manufacturing, education, biotech, health, and more. The possibilities are many.

Easy Vidra Eze is the managing partner of Remagine Ventures, a seed fund that invests in aspiring founders at the intersection of tech, entertainment, gaming and commerce, with a spotlight on Israel.

I am a former general partner at Google Ventures, head of Google for Entrepreneurs in Europe, and founding head of Campus London, Google’s first physical center for startups.

I’m also the founder of Techbikers, a non-profit organization that brings together the startup ecosystem on cycling challenges in support of Room to Read. Since our founding in 2012, we have built 11 schools and 50 libraries in developing countries.

Easy VidraEaz Vidra Latest Posts (View All)

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