Quarterly Reading 0x12

2017-05-01Home

The weekly reading has been held off since Feb 27th, bypassing Biweekly, Monthly and finally to Quarterly. My Pocket list has been piling up (125 read-it-later) and I can no longer pretend the world doesn't change. It is revolving super fast. Unlike previous readings where we dived into technique details, we will look more from outside this time.

Acquisition

While the big fish looks to fill in the missing part of its software stacks, the small fish seeks for sustainably growth and profit.

  • Mozilla Acquires Pocket. Pocket started out as a Firefox add-on and finally has become part of it. Let's see how the integration could go deeper after the acquisition.

  • Kaggle joins Google Cloud.

    Founded in 2010, Kaggle is home to the world's largest community of data scientists and machine learning enthusiasts.

    This could make deployment of machine learning algorithms much easier.

  • Gitter has been acquired by GitLab.

    Next piece of wow: we will be open sourcing all of the Gitter.

    Gitter will be like GitLab, which allows you to setup your own GitHub.

Business story

Another topic I rarely mention but is worth bringing up.

Releases

Road Ahead

  • Five AI Startup Predictions for 2017 by Bradford Cross, who has been working with AI for nearly 20 years, and building silicon valley AI startups for nearly 10 (which leads to the fifth point).

    • Bots go bust.

      the current mania around ‘bots’ defined as conversational interfaces over voice and chat will begin its collapse in 2017

    • Deep learning goes commodity

      I am suggesting that deep learning will become more commodity among machine learning people this year, but i am not suggesting that machine learning itself will become commodity.

    • AI is Cleantech 2.0 for VCs

      the batch that are diving in at the top of this pre-mania are making the same mistake that cleantechs did -- they are diving into AI instead of diving into a customer need.

    • MLaaS dies a second death

      the people that know what they’re doing just use open source, and the people that don’t will not get anything to work, ever, even with APIs

    • Full stack vertical AI startups actually work

      Vertical AI startups solve full-stack industry problems that require subject matter expertise, unique data, and a product that uses AI to deliver its core value proposition.