How to accelerate your path to AI

  • “Gartner believes that the future of analytics is augmented. That is, analytics will be AI-driven and all end-to-end use cases will be automated.
  • The biggest difference between the development of AI and other software platforms is the speed of the transition. While ERP platforms took decades to reach this stage, AI has probably had the fastest transition from in-house R&D to mass market that we’ve seen in software development.
  • The biggest opportunity for you right now is to accelerate the process of bringing AI into your product at the lowest cost possible. Rather than investing in creating your own AI capability, get to market much quicker and cheaper by purchasing a black box that someone else has built and embed it into your own application.”

https://www.linkedin.com/pulse/how-accelerate-your-path-ai-glen-rabie

2019 AI eCommerce Spotlight Awards

2019 “AI eCommerce Spotlight Award”

Today, I’m proud to announce the 2nd annual “AI eCommerce Spotlight Award” winners. These awards are distributed to recognize those companies that have differentiated themselves from the competition over the prior 12 month period within the ai eCommerce industry.

This year we’re recognizing 4 companies with GOLD and SILVER awards.

To determine the winners, we developed a matrix of factors with individual weights. The scores were then tallied and vendors were stack-ranked by overall performance.

Spotlight_Gold_Small

GOLD Winners

  • Cognitive Scale
  • Sentient

Spotlight_Silver_Small

SILVER Winners

  • Apptus
  • Boxx

Congratulations to our winners. We’ll be closely monitoring and reporting on the performance of all vendors, existing and new, throughout the course of the year.

A list of all vendors that were considered for the awards include:


Sentient – https://www.sentient.ai

Cognitive Scale – https://www.cognitivescale.com

Apptus – http://www.apptus.com

Boxx.ai – http://m.boxx.ai/#home

Albert.ai – https://albert.ai

DynamicYield – https://www.dynamicyield.com

Bloomreach – https://www.bloomreach.com/en

Twiggle – http://www.twiggle.com

Emarsys – https://www.emarsys.com/en/

Braze (Formerly Appboy) – https://www.braze.com/product/optimization-ai/

Nosto – https://www.nosto.com

Limespot – https://www.limespot.com/

Listrak – https://www.listrak.com

Personali.com – http://www.personali.com/

Triggmine – https://triggmine.io/

ChatKit – https://chatkit.com/

SearchIQ – https://www.searchiq.co/

CloudFlare – https://www.cloudflare.com/

Reflektion – http://reflektion.com

Zeta (Formerly: BoomTrain) – https://boomtrain.com

Cloud-iq – http://www.cloud-iq.com

Neowise – http://www.neowize.com

LiftIgniter – https://www.liftigniter.com

WACUL – https://wacul-ai.com/en/

Choice.ai – https://choice.ai

Scaled Inference – https://www.scaledinference.com/index.html

Staqu – http://www.staqu.com

Visenze – https://www.visenze.com

Infinite Analytics – http://infiniteanalytics.com

Layer6.ai – https://layer6.ai

Msg.ai – http://msg.ai/#home

WEVO – https://www.wevoconversion.com

Wylei – http://wylei.com

Granify – https://www.granify.com

Reactful – https://www.reactful.com

Couture.ai – http://www.couture.ai

Klevu – https://www.klevu.com

The Current State of Machine Intelligence 1.0 to 3.0 – shivonzilis.com

Used_ShivonZilis.png

“Almost a year ago, we published our now-annual landscape of machine intelligence companies, and goodness have we seen a lot of activity since then. This year’s landscape has a third more companies than our first one did two years ago, and it feels even more futile to try to be comprehensive, since this just scratches the surface of all of the activity out there.

As has been the case for the last couple of years, our fund still obsesses over “problem first” machine intelligence—we’ve invested in 35 machine intelligence companies solving 35 meaningful problems in areas from security to recruiting to software development. (Our fund focuses on the future of work, so there are some machine intelligence domains where we invest more than others.)”

Read full post and view infographic: http://www.shivonzilis.com

Build, buy, or both? The AI implementation conundrum – Pedro Alves, Ople

“Let’s assume you are in ecommerce, and you’re interested in predicting the likelihood of a customer checking out her shopping cart. If you are making the prediction based on factors like the previous purchase history and time spent on site, you will get a reasonable outcome. But if you are looking at factors like the number of red cars on the street at the time or the number of windows in your office, you will never get a reliable answer.

This example is somewhat extreme, but the point is that AI is not magic. Moreover, it requires your expertise because the answers to what matters are often industry- and even company-specific. In other words, you need to rally your teams and figure out the questions and answers you seek before embarking on any AI venture.”

https://www.google.com/amp/s/venturebeat.com/2018/10/01/build-buy-or-both-the-ai-implementation-conundrum/amp/