Intel, Google, GE, And Samsung Among Most Active Corporate Investors In AI Startups

Intel, Google, GE, And Samsung Among Most Active Corporate Investors In AI Startups

  • Google Ventures , which backed over 10 unique companies, ranked second as an active investor in AI.
  • As we earlier reported , Google is also a major acquirer of AI startups.
  • Intel Capital is the most active corporate investor on our list, having backed over a dozen separate unique AI-based companies, including healthcare startup Lumiata , machine-learning platform DataRobot , and imaging startup Perfant Technology .
  • Corporates and their venture capital groups are among the most active investors in this category ( tech corporates have also been active acquirers in the category ).
  • Our artificial intelligence category includes companies applying AI solutions to verticals like healthcare, advertising, and finance as well as those developing general-purpose AI tech.

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@peterxing: “Intel, Google, GE, And Samsung Among Most Active Corporate Investors In AI Startups”


With AI dealmaking exploding recently, corporates and their venture arms have not been left out of the rush.


Intel, Google, GE, And Samsung Among Most Active Corporate Investors In AI Startups

Concrete AI safety problems

Concrete #AI safety problems

  • Advancing AI requires making AI systems smarter, but it also requires preventing accidents – that is, ensuring that AI systems do what people actually want them to do.
  • We think that broad AI safety collaborations will enable everyone to build better machine learning systems.
  • We (along with researchers from Berkeley and Stanford) are co-authors on today’s paper led by Google Brain researchers, Concrete Problems in AI Safety .
  • Many of the problems are not new, but the paper explores them in the context of cutting-edge systems.
  • The paper explores many research problems around ensuring that modern machine learning systems operate as intended.

Read the full article, click here.


@RickKing16: “Concrete #AI safety problems”


We (along with researchers from Berkeley and Stanford) are co-authors on today’s paper led by Google Brain researchers, Concrete Problems in AI Safety. The paper explores many research problems around ensuring that modern machine learning systems operate as intended. (The problems are very practical, and we’ve already seen some being integrated into OpenAI Gym.)


Concrete AI safety problems

How Behavioral Economics Helps Entrepreneurs—and March Madness Pickers

#BigData? #IoT? #AI?
How #BehavioralEconomics Helps Entrepreneurs

#fintech #startup #biases

  • But choice architecture’s actual point is to help consumers more easily get to the choice that best serves them .
  • So now let’s take a moment to look at how understanding behavioral economics can be essential in helping entrepreneurs become better business leaders-and March Madness pickers.
  • The good news for entrepreneurs-and bracket pickers-is that data science and well-structured teams can help us “think slower” and ameliorate such cognitive biases.
  • Market data provided by Interactive Data .
  • In one experiment conducted at a racetrack, gamblers were asked how confident they were in their bets either immediately before or after placing their bets; those polled afterward were significantly more confident in their choice than those asked beforehand.

Read the full article, click here.


@andi_staub: “#BigData? #IoT? #AI?
How #BehavioralEconomics Helps Entrepreneurs

#fintech #startup #biases”


Behavioral economics explains a lot of the biases that distort the choices made by entrepreneurs and March Madness bracket pickers.


How Behavioral Economics Helps Entrepreneurs—and March Madness Pickers

Machine Learning for Designers

[NEW] Free Report: #MachineLearning for Designers @PatrickHebron   #OReillyDesign

  • Machine learning is no longer just a tool for data scientists.
  • The O’Reilly report not only introduces you to contemporary machine learning systems, but also provides a conceptual framework to help you integrate machine-learning capabilities into your user-facing designs.
  • Stay up to date with advancements in the field and spot emerging opportunities for machine learning-aided design
  • You’ll learn how recent advancements in machine learning can radically enhance software capabilities through natural language processing, image recognition, content personalization, and behavior prediction.
  • Using tangible, real-world examples, author Patrick Hebron explains how machine-learning applications can affect the way you design websites, mobile applications, and other software.

Read the full article, click here.


@oreillydesign: “[NEW] Free Report: #MachineLearning for Designers @PatrickHebron #OReillyDesign”


Machine learning is no longer just a tool for data scientists. By taking advantage of recent advances in this technology, UI and UX designers can find ways to better engage with and understand their users. This O’Reilly report not only introduces you…


Machine Learning for Designers

Benchmarking CrunchBase’s Top 25 Artificial Intelligence Startups

Check them out

Benchmarking @crunchbase 's Top 25 #AI Startups 

 #fintech

  • “You are not born with a fixed amount of resilience.
  • It’s a muscle, you can build it up, and then draw on it when you need it.”
  • Quote of the Day
  • Sheryl Sandberg

Read the full article, click here.


@SpirosMargaris: “Check them out

Benchmarking @crunchbase ‘s Top 25 #AI Startups

#fintech”


iCarbonX, Anki, CARMAT, Arago, CloudMinds, Zero Zero Robotics, Preferred Networks, Inc., CustomerMatrix, Ozlo, and Scaled Inference are the top 10 Artifical Intelligence startups based on an analysis of CrunchBase data today. Artificial Intelligence (AI) is one of the most diverse startup categories in CrunchBase, with 256 startups distributed across 225 categories […]


Benchmarking CrunchBase’s Top 25 Artificial Intelligence Startups

GitHub

Hands-on #machinelearning labs on @github? Oh, yeah, we got that!

  • Evaluate a Binary classification model
  • Consume the ML Web Service in a C# application
  • Comparing two binary classification model
  • Publishing a trained model as Web Service
  • Lab4 – Develop and Consume AzureML Models

Read the full article, click here.


@MicrosoftR: “Hands-on #machinelearning labs on @github? Oh, yeah, we got that!”


hol-azure-machine-learning – Introduction to Machine Learning and Azure Machine Learning Services. Hands on labs to show Azure Machine Learning features, developing experiments, feature engineering, R and Python Scripting, Production stage, publishing models as web service, RRS and BES usage


GitHub

ICYMI: Deep learning computers decode human interactions

ICYMI: Deep learning computers decode human interactions

  • CRISPR gene-editing approved for first human trials
  • ICYMI: Deep learning computers decode human interactions
  • A vision system watched 600 hours of TV to learn when two people are going to hug.
  • SharePoint for iOS helps you take your work on the road.
  • NASA debuts new internet technology aboard the ISS

Read the full article, click here.


@engadget: “ICYMI: Deep learning computers decode human interactions”


Today on In Case You Missed It: MIT researchers made a deep learning vision system watch TV and it learned to predict when people are going to kiss, shake ha…


ICYMI: Deep learning computers decode human interactions