Latest Generative AI news and analysis from startup Europe

Hundreds of new startups are rushing into the market to develop foundation models, build AI-native apps, and stand up infrastructure/tooling. Over the last couple of years, we’ve seen a new wave of AI applications built on top of or incorporating large foundation models. This trend is commonly referred to as generative AI, because the models are used to generate content (image, text, audio, etc.), or simply as large foundation models, because the underlying technologies can be adapted to tasks beyond just content generation. Founded in 2021, Zibra AI aims to use the funding to expand its team and accelerate the growth of its generative AI technology. This includes its flagship product, Zibra Effects, a Unity Verified Solution available on a variety of platforms which has use cases in industries such as gaming, the metaverse, and professional training. The solution automates the creation of 3D assets and visual effects, streamlining production for developers.

When using materials from the site must provide a hyperlink within the first paragraph on the page layout of the original article, indicating the publication brand AIN.CAPITAL. Right now all these tools, such as DALL-E, Midjourney, ChatGPT and so on are free, but there’s no guarantee how long that will last. “There won’t be software companies that aren’t AI-powered in three to five years,” says Roetzer. That has big implications for anyone who runs or invests in software companies.

Top 10 games industry jobs to apply for this week

Looking ahead, Andreessen predicts that these tech-savvy youngsters, armed with over a decade of AI experience by the time they reach adulthood, will have a profound understanding of how to leverage AI to their advantage. Unlike older generations, who are navigating the integration of AI into their lives for the first time, this future generation Yakov Livshits is expected to be proficient in seeking AI-based help and making the most of AI resources at their disposal. This article was initially compiled by an advanced AI, engineered to extract, analyze, and organize information from a broad array of sources. It operates devoid of personal beliefs, emotions, or biases, providing data-centric content.

This ability to remember past exchanges leads to distinct narratives for each AI character, further enhancing the realism and complexity of the virtual environment. This post is a deep dive into the sustainable differentiation that results in a compounding flywheel, with a focus on financial services companies that sell commodity-like, nonphysical world products such as money, insurance, lending, or equity capital. As it happens, this was a central claim of Marxism, that the owners of the means of production – the bourgeoisie – would inevitably steal all societal wealth from the people who do the actual  work – the proletariat. This is another fallacy that simply will not die no matter how often it’s disproved by reality. An AI copilot could enable any player to be a Master Builder in a UGC game – providing step by step instructions in response to a text prompt or image, and coaching players through mistakes.

Pahdo Labs Raises $15M to Let Players Make Anime Games With AI Tools

A16z General Partner Alex Rampell on how a “consumer-signup robotic process automation (RPA)”—which AI can do—is the missing link to changing how friction/inertia preserves giant gross-profit pools in financial services. Additionally, if these third-party payment links allow developers to bypass Apple’s 30% take rate, developers could potentially deliver more value back to customers and drive greater loyalty. For the first time in more than a decade, Apple’s stronghold on app distribution and monetization may be threatened, as a U.S. appeals court confirmed in April 2023 that Apple can no longer prevent third-party payment links in the App Store. The development of AI started in the 1940’s, simultaneous with the invention of the computer. The first scientific paper on neural networks – the architecture of the AI we have today – was published in 1943.

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.

Generative AI is a category of machine learning where computers can generate original new content in response to prompts from the user. Today text and images are the most mature applications of this technology, but there is work underway in virtually every creative domain, from animation, to sound effects, to music, to even creating virtual characters with fully fleshed out personalities. We’re in the early days of this market, and we don’t know how much of this delta consumers will pay and how much will accrue to consumer surplus. Right now, however, we’re seeing consumer AI apps commonly charge a 2–3x premium over their non-AI equivalents. While it’s possible that AI apps will cost the same as existing apps over time, consumers may pay the existing digital price plus some portion of the delta between the current digital and in-person prices. To illustrate the potential size of this total opportunity—consumer surplus included—let’s estimate that consumers would pay half of what they currently pay for in-person services.

We are incredibly bullish on generative AI and believe it will have a massive impact in the software industry and beyond. The goal of this post is to map out the dynamics of the market and start to answer the broader questions about generative AI business models. For our dollar, generative AI holds a similar promise when it comes to the cost and time of generating content—everything from writing an email to producing an entire movie. Of course, all of this assumes that AI scaling continues and we continue to see massive gains in economics and capabilities. As of this writing, many of the experts we talk to believe we’re in the very early innings for the technology and we’re very likely to see tremendous continued progress for years to come. The occupations and industries impacted by the economics of AI expand well beyond the few examples listed above.

There are technical hurdles to overcome, but as companies introduce multi-modality and improve model memory, latency, and steering, they can tailor their services to each individual’s preferences and usage over time. Copywriting and ad-generating apps powered by LLMs have already seen great results, leading to quick uptake among marketers, advertisers, and scrappy entrepreneurs. Currently, however, most LLM outputs are relatively generalized, which makes it difficult to leverage them for use cases requiring personalization and contextual understanding. It’s often not feasible or desirable to fine-tune a model for every individual user. We also expect to see more professional, even clinical, use cases for AI chatbots.

This adaptability and contextual understanding are seen as foundational aspects that make AI accessible to all individuals. Before you can run the app, you will need to make sure the convex functions are deployed to its production environment. “Just as Git revolutionized software Yakov Livshits development, Story Protocol is transforming the development of creative IP,” said Simon Kim, CEO and Managing Partner at Hashed. With the rise of platforms like OpenAI’s ChatGPT, the digital world has witnessed a surge in remixes and mashups, sparking copyright lawsuits.

This compares to 70% paid traffic for the bottom quartile of non-AI consumer subscription companies, per a16z’s benchmarking of 150 products. The below graph shows the differential in traffic between the #1 and #2 players in each space. While there are some exceptions (e.g., companionship), for most categories there is less than a 2x gap—meaning the top company receives just double (or less) the number of visits as its next closest competitor. This is nowhere near insurmountable given companies on the list averaged 50% monthly growth over the past 6 months. Compared to mainstream consumer products, even the biggest GenAI products are still fairly small. When combining web and mobile app traffic, ChatGPT ranks around the same scale as Reddit, LinkedIn, and Twitch—but still far below the “giants” (WhatsApp, YouTube, Facebook, etc.).