Tom Tunguz
JUNE 5, 2023
90% of startups have plans or have released an AI feature, 54% of those features will launch in 2023, but only 30% of companies are hiring new people to do it, according to ProductBoard’s survey. These figures highlight three points: AI has become an essential product component for most software companies.
Intercom, Inc.
SEPTEMBER 9, 2022
GPT-3 can create human-like text on demand, and DALL-E, a machine learning model that generates images from text prompts, has exploded in popularity on social media, answering the world’s most pressing questions such as, “what would Darth Vader look like ice fishing?” AI has been quite overhyped in the past. Paul, how are you?
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Tom Tunguz
JANUARY 17, 2019
I’ve started to call them AI Agencies. AI Agencies use machine learning to disrupt a market dominated by agencies. Often, these startups begin as software companies selling machine learning software into agencies. The startup leverages machine learning under the hood.
Tom Tunguz
MARCH 30, 2023
As generative AI captivates Startupland, startups will do what they have always done: integrate new technology to build transformative businesses. Incumbents have seized the moment with Microsoft, Adobe, & others integrating generative AI into their products quickest. What are these moats? More users means a better product.
Advertiser: Data Robot
By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the whitepaper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.
SaaStr
DECEMBER 8, 2023
Hear the latest insights on AI from leading investor and SaaStr fan-fave, Tomasz Tunguz of Theory Ventures. LLMs are transforming the way people use software, and these AI and data-driven companies share first-hand how they’re seeing this change take place. AI expertise might take a couple hundred top AI researchers to train them.
Tom Tunguz
JULY 4, 2022
Last week, I installed Github’s Copilot , a machine learning tool that helps engineers write software. I use applied AI elsewhere. Two distinct machine learning systems have analyzed this blog post for grammatical errors, clichés, brevity, style, and weasel words. They have it wrong.
Advertiser: Data Robot
By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the white paper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.
Advertiser: Data Robot
Across all sectors, companies are learning that they can transform their businesses by embracing Intelligent Process Automation, or IPA. With the pairing of AI and RPA, IPA adds a new layer of intelligent decision-making processes to automated RPA tasks. What is AI? What is IPA? Common IPA use cases.
Advertiser: Data Robot
But we can take the right actions to prevent failure and ensure that AI systems perform to predictably high standards, meet business needs, unlock additional resources for financial sustainability, and reflect the real patterns observed in the outside world.
Advertiser: Data Robot
Many organizations are dipping their toes into machine learning and artificial intelligence (AI). Download this comprehensive guide to learn: What is MLOps? Why do AI-driven organizations need it? How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects?
Advertiser: Data Robot
For businesses that are AI-driven, this trust hinges on the confidence that their AI solution can help them make their most critical decisions. In our eBook, Building Trustworthy AI with MLOps, we look at how machine learning operations (MLOps) helps companies deliver machine learning applications in production at scale.
Advertiser: Data Robot
You know you want to invest in artificial intelligence (AI) and machine learning to take full advantage of the wealth of available data at your fingertips. But rapid change, vendor churn, hype and jargon make it increasingly difficult to choose an AI vendor. The five key things to consider when looking for an AI vendor.
Advertiser: Data Robot
The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. Numerous high-profile examples demonstrate the reality that AI is not a default “neutral” technology and can come to reflect or exacerbate bias encoded in human data. Are you ready to deliver fair, unbiased, and trustworthy AI?
Advertiser: Data Robot
AI is becoming ubiquitous. More and more critical decisions are automated through machine learning models, determining the future of a business or making life-altering decisions for real people. The number of critical touch points is growing exponentially with the adoption of AI. Brought to you by Data Robot.
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