Half Ideas – Startups and Entrepreneurship takes a closer look at GPT-3 and what it means for AI.

GPT 3 can write poetry, translate text, chat convincingly, and answer abstract questions. It’s being used to code, design and much more. I’ll give you a demo of some of the latest in this technology and some of how it works.

GPT 3 has been developed for a number of years. One of the early papers published was on Generative Pre-Training. The idea behind generative pre-training (GPT) is that while most AI’s are trained on labeled data, there’s a ton of data that isn’t labeled. If you can evaluate the words and use them to train and tune the AI it can start to create predictions of future text on the unlabeled data. You repeat the process until predictions start to converge.   

In this article, Danny Crichton examines the current state of startups and the decline in innovation they are showing.

Every week in my inbox, there is another no-code startup. Another fintech play for payments and credit cards and personal finance. Another remote work or online events startup. Another cannabis startup, another cryptocurrency, another analytics tool for some other function in the workplace (janitor productivity as a service!)

It honestly feels at times like we are stuck: it’s the same rehashes of old software, but theoretically “better” (yes it is a note-taking app, but it runs on Kubernetes!). In fact, that feeling of repetitiveness and the glacial pace of true innovation isn’t just in my head or maybe yours: it’s also been identified by scientists and researchers and remains a key area of debate in the economics of innovation field.

While the world may have been thrown for a loop with the COVID-19, AI startups have a decent chance to weather the economic storm.

Here are some factoids via Forbes.

  • There are 9,216 startups and companies listed in Crunchbase today who are relying on machine learning for their main and ancillary applications, products, and services, a 6% increase from 2019’s 8,705 startups & companies.
  • Artificial Intelligence-related companies raised $16.5B in 2019, driven by 695 deals according to PwC/CB Insights MoneyTree Report, Q1 2020.
  • Artificial intelligence deals decreased in Q1, 2020, down to 148 deals from 164 in Q4, 2019, according to PwC/CB Insights MoneyTree Report, Q1 2020.

Microsoft for Startups shares this highlight reel from the Spring MLADS conference.

In case you’re not familiar with MLADS, check out Data Driven’s coverage of the most recent one.

Twice a year, Microsoft assembles over 4,000 of our top data scientists and engineers for a two day internal conference to explore the state of the art around machine learning and data science.

Earlier this year, 30 leading startups who are active in the Microsoft for Startups program came to showcase their solutions and engage directly with the engineering teams.

Artificial Intelligence and Machine Learning are the latest in a long line of tech-worthy buzzwords.

Given the hype, it is often difficult to separate the technology from the marketing. Entrepreneurs need to understand what the technology actually does and the problems it solves.

In this talk by Seth Juarez, learn how AI and ML work, the kinds of problems it solves, and what the implications of its use are for your startup.

Armed with this practical knowledge, you’ll be able to make better decisions about where to start and how you can use machine learning and AI in your businesses.

For more information head over to https://aka.ms/aidevresources

Digitalization leads our world in a new are of technology.

Technology in Health-care is extremely important.

Fouad Al-Noor will teach you how to build a successful medical start up step by step: so that you don‘t have to fall in the Medtech Valley of Death.

Fouad has a masters in Electric Engineering with Nanotechnology from the University of Southampton. He worked as a research assistant at Imperial College London before joining Entrepreneur First.

He wrote his thesis on paper-based medical diagnostics using image processing.