Sequoias Sonya Huang: Generative AI hype absolutely justified
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All are building products that depend on one thing – consumers’ ability to securely share their data to use different services. When we look across the Intuit QuickBooks platform and the overall fintech ecosystem, we see a variety of innovations fueled by AI and data science that are helping small businesses succeed. By efficiently embedding and connecting financial services like banking, payments, and lending to help small businesses, we can reinvent how SMBs get paid and enable greater access to the vital funds they need at critical points in their journey. This presents a tremendous opportunity that innovation in fintech can solve by speeding up money movement, increasing access to capital, and making it easier to manage business operations in a central place.
Generative AI was in the background on last year’s list but in the foreground now. While most of the traditional solutions are rule-based, multimodal LLM models can collate unstructured physician notes, lab panels, and imaging to determine the right diagnosis codes. Automation can also reduce the administrative back and forth with payors and will be a natural lead into the massive opportunity that is revenue cycle management. Incumbents in the documentation space will also have a formidable advantage here. Prior authorizationPrior authorization is the arduous process insurance companies impose on physicians to seek approval before they can prescribe certain drugs to a patient or schedule certain procedures. In 2021, physicians submitted more than 35 million prior authorization requests to Medicare Advantage payors, of which 2 million were denied.
For developers who had been starved of access to LLMs, the floodgates Yakov Livshits are now open for exploration and application development.
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Then the other big category where there has been a lot has been in the text space. So there’s a lot of these marketing Gen AI companies, and some of them are really working. We’re seeing it evolve, as well, where people started from shorter-form generations and now we’re getting really, really long form.
We are of significant enough scale that we, of course, have good purchasing economics of things like bandwidth and energy and so forth. So, in general, there’s significant cost savings by running on AWS, and that’s what our customers are focused on. The conversation that I most end up having with CEOs is about organizational transformation. It is about how they can put data at the center of their decision-making in a way that most organizations have never actually done in their history.
And it’s about using the cloud to innovate more quickly and to drive speed into their organizations. Those are cultural characteristics, not technology characteristics, and those have organizational implications about how they organize and what teams they need to have. It turns out that while the technology is sophisticated, deploying the technology is arguably the lesser challenge compared with how do you mold and shape the organization to best take advantage of all the benefits that the cloud is providing. Open finance has supported more inclusive, competitive financial systems for consumers and small businesses in the U.S. and across the globe – and there is room to do much more. As an example, the National Consumer Law Consumer recently put out a new report that looked at consumers providing access to their bank account data so their rent payments could inform their mortgage underwriting and help build credit.
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.
Well, I would be alarmed if the hype was really high and the results weren’t there. The hype is high, and I think part of that is, again, people emotionally want to attach onto something that gives them hope and optimism, but the results are there as well. I’ll go back to “writing 40% of people’s code” example — that is phenomenal both technological progress as well as economic value delivery. I think it’s absolutely justified given the results that we’re seeing. My hope is actually that by putting out this landscape, we plant that seed and a lot of future founders that have been trying to figure out what to build next, I think it’s wonderful to draw them to this.
Secure AI served directly on your machine is a massive leap forward in space. With Gan.ai’s studio-quality video personalization software, brands simply need to record a video once, add dynamic keywords to a script, and Gan.ai will generate millions of hyper-customized videos in one click. There are many new opportunities with the rise of generative technology. Generative technology has the potential to increase efficiency for marketers, improve creativity for designers, enable more distribution channels for content creators, and create new opportunities for many, many more.
- New startups continue to enter the market at a swift pace, supported by advances in generative infrastructure like large language models and vector databases.
- For example, fintech is enabling increased access to capital for business owners from diverse and varying backgrounds by leveraging alternative data to evaluate creditworthiness and risk models.
- It wasn’t just a joke that the article was co-written with GPT-3; it actually was.
- Runway generates, edits and applies effects to video that met the quality bar for the Oscar-winning team behind Everything Everywhere All at Once.
- The company has built its own model called Luminous and has put a lot of emphasis on combating hallucination and researching ways to make its systems more reliable.
Gan.ai is solving a pressing need for businesses as video becomes the go-to means in engaging users. The amount of online video people are watching has almost doubled since 2018, and an overwhelming Yakov Livshits 86% of businesses use video as a marketing tool. However, creating videos can often be a time-consuming process which lacks personalization when it comes to targeting a large audience.
Sequoia Capital has emerged as the most active investor in the generative AI space since 2017, having invested in more generative AI startups than any other investor. Other significant investors include Andreessen Horowitz and Khosla Ventures. Despite these impressive figures, the generative AI space is still in its early stages. Out of over 360 identified generative AI companies, 27% have yet to secure any outside equity funding, and over half are at the Series A stage or earlier, indicating the immense growth potential.
It means that anyone can use the system – even to do something like programming a computer. In terms of the applications, there are already plenty of examples where companies have enhanced their platforms with generative AI. But in the coming months, there will likely be entirely new products.
Nokleby, who has since left the company, said that for a long time Lily AI got by using a homegrown system, but that wasn’t cutting it anymore. And he said that while some MLops systems can manage a larger number of models, they might not have desired features such as robust data visualization capabilities or the ability to work on premises rather than in cloud environments. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB.
Per TechCrunch, Gan.ai’s video personalisation software allows brands to record a video, input dynamic keywords into a script, and produce millions of uniquely customised videos. Ycombinator is by a large margin the most active accelerator for GenAI startups, with over 100 startups supported, including OpenAI, Jasper and Replit. Verticalized model makers are starting to emerge, such as Hippocratic.ai, which came out of stealth with a $50M seed round for its health-focused LLM. Industries poised for specifically developed LLMs include health, fintech, and legal tech.
For instance, the European Union’s General Data Protection Regulation (GDPR) encompasses the “right to explanation,” allowing individuals to demand clarifications for automated decisions made about them. The Algorithmic Accountability Act proposes that companies conduct impact assessments of their high-risk AI systems in the US. Biases in AI, whether unintentional or a byproduct of training data, can lead to discriminatory outcomes, potentially violating such regulations.