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The Non-Technical Guide to Machine Learning & Artificial Intelligence

Cyber Security | August 28, 2021

One of the major promises of AI is freeing people from mindless tasks, so they can do more meaningful work. When we’re not writing posts about AI, we’re building Journal to help you see and search your private work information, all in one place.

Below, you can find links to the 317+ companies in the landscape (and a few more), and play around with some apps that are applying machine learning in interesting ways.

Enterprise Intelligence

Visual

Audio

Sensor

Internal Data

Market

Enterprise Functions

☎️Customer Support

Sales

Marketing

Security

Recruiting

Autonomous Systems

Ground Navigation

✈️Aerial

Industrial

Agents

Personal

Professional

Industries

Agriculture

Education

Investment

Legal

Transportation/Logistics

Materials

Retail Finance

Healthcare

Patient

Image

Biological

Technology Stack

Agent & Conversational Interfaces

Data Science

Machine Learning

Natural Language

Development

Data Capture

Open Source Libraries

Hardware

Research

People to Know in Machine Learning and AI

Chief Scientist of Baidu; Chairman and Co-Founder of Coursera; Stanford CS faculty.

President, YC Group, OpenAI co-chairman.

CEO of Journal. Former Data Engineering Lead at Mattermark.

Google Senior Fellow at Google, Inc. Co-founder and leader of Google’s deep learning research and engineering team.

Computer scientist and E. Fredkin University Professor at the Carnegie Mellon University.

The Principal Data Scientist at Booz Allen, PhD Astrophysicist.

Research scientist at OpenAI. Previously CS PhD student at Stanford.

Former VP of Data Jawbone & LinkedIn data scientist.

Professor of Computer Science, Stanford University, Director of Stanford AI Lab.

Associate Professor in Computer Science at London’s Global University.

University Lecturer in Engineering Science at the University of Oxford.

Associate Professor, UC Berkeley, EECS. Berkeley Artificial Intelligence Research (BAIR) laboratory. UC Berkeley Center for Human Compatible AI. Co-Founder Gradescope.

SlackData Engineering and Apache Crunch committer.

Head of Search, Learning, & Intelligence at Slack in NYC. Former SVP of Product at foursquare + Google PM on structured search.

Senior Data Scientist at Penn Institute for Biomedical Informatics.

Partner at Bloomberg Beta where she focuses on machine intelligence companies.

Founder of @TweneyMedia, former EIC @venturebeat, ex-@WIRED, publisher of @tinywords.

Head of Data Science / CTO Office at Bloomberg LP.

Cloud investor at Emergence Capital, cloud entrepreneur.

Strategy and Communications Director OpenAI. Past: @business World’s Only Neural Net Reporter. @theregister Distributed Systems Reporter.

Data Scientist, Berkeley Institute for Data Science.

Director of AI Research, Facebook. Founding Director of the NYU Center for Data Science

. Professor of computer science at UW and author of ‘The Master Algorithm’.

. Unapologetic abuser of the machine BYOR.

. AI Policy Research Fellow, Future of Humanity Institute, Oxford. PhD candidate, Human and Social Dimensions of Science and Technology, ASU.

. Founder & Organizer, New York Artificial Intelligence (NYAI).

Program Chair, O’Reilly Artificial Intelligence Conference.

Assistant Professor at Johns Hopkins University. Expertise in machine learning, streaming data and health informatics.

Researcher and Professor of Information Engineering at the University of Cambridge.

Professor of Computer Science at Stanford, Co-Founder of Coursera.

Leads and provides thought leadership for the Global IBM Watson Artificial Intelligence Xprize prize.

General Manager, Fuse Labs, Microsoft Research.

Chief Scientist and Co-Founder, Deepmind.

Artificial Intelligence and ML Events

Machine Learning and Artificial Intelligence News Sources

✉️Weekly Emails:

Websites:

Machine Intelligence Startups & Tools

NYAI has managed to rise above the noise and organize ~1,500 researchers, students, founders, and investors who are genuinely awesome people.

The impacts that machine learning and AI have on our world will not be felt in isolation. These changes will affect all of us. NYAI’s monthly events are the best way, that I’ve found so far, to learn about, collaborate on and network over emerging trends in artificial intelligence.

This content was originally published here.