Frank Chen at AI Frontiers: Startups and AI

FRANK CHEN

Artificial Intelligence

@withfries2 [email protected]

Surveying The Startup Landscape

©2017 Andreessen Horowitz. Proprietary and confidential.

Databases Got Inside All Software


So Will AI



20162009

Mobile First

2007

Cloud Native AI Inside


20031995

Internet Architecture

1993

Client-Server Virtual Appliance


Transition Subtitle Goes Here

What Can Startups Do?


See in the Real World


Seeing Things in the World

COMPANY | ORGANIZATION:

DESCRIPTION:

TECHNIQUES:

Image recognition,image segmentation, and visual similarity search

What’s similar to this thing in the picture?


Automated Analysis of Drone Imagery

Image segmentation, flight planning, grade analysis

Safety compliance, maximize fuel efficiency, calculate stockpile volumes, recognize storm damage


DESCRIPTION:

TECHNIQUES:


Understand Language


Help Lawyers Win Trials

Logistic Regressions, SVM, Long Short-Term Memory Convolutional Neural Nets

Train new prediction models, identify documents relevant for a trial by topic, translate documents into other languages, audio transcription


DESCRIPTION:

TECHNIQUES:


Hear the Voice of the Customer

Topic modeling with BigARTM, NLP, opinion mining and sentiment analysis, deep learning (LSTM, Unsupervised Sentiment Neuron) with Keras and Tensorflow

Automatically detect themes and sentiment in customer reviews


DESCRIPTION:

TECHNIQUE:


Make Predictions


Help Airbnb Hosters Price Their Pads

https://www.blog.google/products/gmail/save-time-with-smart-reply-in-gmail/

Image analysis, Aerosolve open source project

Predict probability of getting a booking based on price, date, photos, location, unique listing features


DESCRIPTION:

TECHNIQUES:


Surface The Best Tips And Photos


Support vector machines, sentiment analysis, spam detection, k-nearest neighbor

Rank tips, group photos, figuring out whether you’re near a venue


DESCRIPTION:

TECHNIQUES:


Figure Out Best Distribution Outlet for a Story

Logistic Regressions, Word Embeddings, Recurrent Neural Networks on Elastic Map Reduce, RedShift, BigQuery

Figure out initial offsite distribution channel for item, and how to optimally route it across channels. Content adaptation and translation.


DESCRIPTION:

TECHNIQUES:


Collect Groceries as Fast as Possible

Gradient boosted decision trees, deep learning with TensorFlow and Keras

8% improvement to pick up times


DESCRIPTION:

TECHNIQUE:


Search For Anti-Aging Drugs

http://blogtacular.com/wp-content/uploads/2016/03/Pinterest-Visual-Search-Zoom-4.png

Used machine learning techniques to filter through 14k metabolites and found a set of 171 metabolites that are predictive of mortality

This subset of metabolites can be used to develop anti-aging drugs and screen for efficacy


DESCRIPTION:


Predict Health Problems

Detect atrial fibrillation using data from your smartwatch


DESCRIPTION:

Deep neural networks, reinforcement learning

TECHNIQUES:


Self-Drive, Self-Fly, Self-Map…


TECHNIQUES:

Map Inside of a Building

https://www.cnet.com/news/youtube-auto-caption-1-billion-videos-subtitles-hearing-impaired/

Vision/face recognition, Simultaneous Localization and Mapping (SLAM), path planning


DESCRIPTION:

Flies inside buildings, constructs 3D maps, identifies people


Drive Taxis


Vision recognition, SLAM, motion planning, vehicle control

Self driving taxi service live in San Jose Villages


DESCRIPTION:

TECHNIQUES:


Self-Fly And Drop Off Blood


Motion planning, navigation

110 kph

75 km delivery radius

30 minute fulfillment time

500 deliveries/day

1.5 kg payload


DESCRIPTION:

TECHNIQUES:


Provide Infrastructure (Picks & Shovels)


Provide Data Analytics Platform


TECHNIQUE:

Apache Spark MLlib (classifications, data prep, regressions, random forest, decision trees, XGBoost…), Scit-kit Learn, Visuatlizations

DESCRIPTION TEXT

Built on Spark, Databricks enables ML teams to run experiments at scale


Auto-Tune Your Existing Models


TECHNIQUE:

“AI for AI” using ensemble of Bayesian and global optimization strategies to perform black-box optimization ( just looks at configs and outputs, not data or model)

DESCRIPTION TEXT

Optimization as a Service that bolts on top of an existing ML or AI pipeline to automatically and optimally tune it.


HD Mapping for Safe Autonomy


TECHNIQUE:

Sensing via sensor fusion, mapping & localization, ML to add semantics and understand traffic patterns, scale out serving infrastructure

DESCRIPTION TEXT

HD Mapping as Service that creates and locates vehicles on a 3D map with centimeter accuracy at 80 mph

Roundabout

Complicated Intersection

What Do We Look For?Transition Subtitle Goes Here


More specifically: What do we look for in an AI startup

that’s different from the other startups we invest in?


Answer:

Nothing

Big Market



Technical Founders With the Right Kind of Ambition


Product-Market Fit

PRODUCT

MARKET

FIT


Founder-Product Fit


Durable Defensive Moat


Attractive Unit Economics (or Other Operating Metrics)

LTV > CAC = 😀 CAC > LTV = 😩

Fast Growth


If You Are an AI StartupPlease do not let me stump you on the basics

What machine learning techniques are you using?

Why those techniques? How well do they work?

What business benefits can you deliver with those techniques?


©2017 Andreessen Horowitz. Proprietary and confidential.©2017 Andreessen Horowitz. Proprietary and confidential.

Data & Analytics

Frank Chen at AI Frontiers: Startups and AI