Is Machine Learning Overhyped?

Tom Tunguz

Solomo (social local mobile). Mobile-first. 2016 was the year of machine learning. During last quarter of 2016, machine learning research has made huge strides. While some may groan that every pitch deck is littered with the words machine learning or artificial intelligence, I think each deck ought to be. Because over the next five to ten years, nearly every company will use machine learning in some form.

Efficient Merchandising Using Machine Learning Algorithms


Machine Learning and AI are set to assume incredibly prominent roles in the retail sector in the not so distant future. Machine Learning in Retail The retail space is undergoing a paradigm shift with innovative applications being tested out for machine learning and AI.

How Machine Learning Can Benefit Your SaaS Startup

Tom Tunguz

From the millions of Amazon Alexas to the self-driving car, new products are coming to market infused with machine learning. The innovation offered by machine learning techniques are real, and they will changed the SaaS world. How can startups use machine learning to their advantage? There are four broad applications of machine learning: Optimize - this morning, fastest way to travel from Sand Hill Road to South Park in San Francisco is highway 101.

The Key Ingredient to Disrupting with Machine Learning

Tom Tunguz

Which are the ripest areas for startups to disrupt using machine learning? At the core, machine learning/artificial intelligence relies on two key ingredients: advanced algorithms and data sets to train those algorithms. Both of these companies proprietary access to user data have helped them establish market dominance in the online/mobile advertising world.

Mobile App Predictions for 2019

The Marketing & Growth Hacking Publication

Mobile Apps are the major reason why smartphones are persisting. Mobile Apps keep modifying each and every year. There are almost 24 billion mobile devices working worldwide right now. Mobile App Trend Predictions for 2019?—?Digitechtips Then comes Machine Learning.

Mobile Productivity for Normal People

Tom Tunguz

Over the past few weeks, there has been a new refrain among consumer mobile startups that I’ve met with: we’re designing for normal people or normals as Chris Dixon would put it. Second, there is a wave to reinvent and reimagine core applications of the mobile phones.

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Mobile Social Networks: The New Customer Acquisition Powerhouse

Tom Tunguz

There’s a force in mobile app distribution that isn’t talked about much despite its magnitude: mobile social networks. Mobile social nets are becoming the predominant mobile app paid discovery/distribution platforms. Facebook’s mobile revenue will reach $2.5B

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The Need-to-Know Mobile App Marketing Resources for This Year

The Marketing & Growth Hacking Publication

Mobile phone use has increased by more than 4 billion since 2015 , most of which can be attributed to the fact that smartphones are rapidly becoming a technological extension of ourselves. You’ll also want to understand the mobile app category you’re operating in an in-depth way?—?who

WePay’s Week In Payments: AI, Mobile Growth and White House Policy


There are many reasons for this according to The Financial Brand , with some of the biggest including siloed data and an inability to start the process of analyzing data and drawing useful insights from it to kickstart AI and machine learning projects. Mobile Payments Explode in APAC.

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AI Superpowers - A History of Chinese Startups and the Implications for the Future of Startupland

Tom Tunguz

The first is his view of the influence of machine learning in the world. First, the book embraces the idea that machine learning creates monopolies based on data aggregation. One started with PCs and laptops, the other with mobile phones.

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1% of Salesforce's Revenue Makes a Unicorn

Tom Tunguz

Mobile, machine learning, blockchain. Salesforce is worth $113 billion. 1% of $113 billion is $1.13 billion. ServiceNow is worth $34B and Workday is worth $33B. 3% of $33-34B is $1B. Atlassian is worth $20.5B. 5% of $20.5B is $1B. Why am I doing all this simple math you might ask? We have reached a point in SaaS where a small fraction of an incumbent is a billion-dollar company.

The top SaaS companies ruling the East Coast


Bringing them together, we will help them and learn from them in equal measure. Driven by machine learning, Recorded Future’s platform gathers and analyzes information from a large number of sources to help teams make the best decisions.

Announcing the 2019 Class of the Western Union Accelerator Powered by Techstars


A mobile and web based facial recognition platform that validates and authenticates financial transactions. Money Cards allows unbanked teens to request, receive and instantly redeem funds from a mobile device.

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The most exciting Latin American SaaS Startups


Elevator pitch : Rabbot offers intelligent software automation for mobile businesses that need to manage and control in a scalable way their fleet journey. As we have showcased in previous pieces, there are many reasons to be excited about the Latin American SaaS ecosystem.

When Will the Next Wave of UI Advances Happen?

Tom Tunguz

and mobile applications built on iPhone and Android transformed the way users interacted with technology. New machine-learning APIs transcribe speech, categorize text, recognize images, translate words, and predict. Technology innovations swing to a pendulum’s cadence. Sometimes innovations begin with infrastructure changes and reverberate up the stack.

7 Predictions for SaaS in 2018

Tom Tunguz

Machine learning fades as a buzzword. ” Or five years ago, “I invest in mobile.” ” Just as those trends have become ubiquitous to be implicit, so will machine learning. Below are 7 predictions about the startup software ecosystem. How many of them do you agree with? The tax holiday for repatriation creates one of the most active M&A environments of the past ten years. The repatriation holiday is part of the new tax plan.

The Evolution of CRM (And Where it’s Going) in the Future

Sales Hacker

They are cloud-based, AI-driven, and accessible from mobile phones. Having a mere semblance of artificial intelligence or machine learning is no longer enough, nor will it fool tech-savvy users. 6) Mobile is a must. Sales engagement via mobile can be empowering.

State of the Cloud 2019: Europa Edition with Alex Ferrara, Bessemer Venture Partners (Video + Transcript)


Bessemer Venture Partners’ Alex Ferrara takes a look at trends and predictions for the cloud industry in 2019. One of the most popular sessions from SaaStr Annual, this presentation will provides an in-depth look at the cloud computing industry across Europe and globally.

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A Breakthrough in Human Computer Interaction

Tom Tunguz

Andrew Ng, a luminary in the world of machine learning, and his teammates at Baidu, Stanford and University of Washington have developed Deep Speech 2 , a neural network based speech recognition system. They tested the speech and accuracy of the system and compared it to people typing on their mobile phones. This speed advantage will render speech to be the primary form of input to computers, initially with mobile phones, but ultimately with laptops.

Marketing’s Technical Liberation

Tom Tunguz

Mobile is the most immediate catalyst for this change. A handful of startups are bringing these ideas to mobile applications as well. Infer sifts through customer databases and uses machine learning to reduce churn and increase upsell.

The SaaS superstars of the East Coast


Bringing them together, we will help them and learn from them in equal measure. Driven by machine learning, Recorded Future’s platform gathers and analyzes information from a large number of sources to help teams make the best decisions.

Google Marketing Live: An Advertiser’s Take on the Highlights


Chavez opened his speed segment by reminding us that: “even the best ads may not perform if your landing pages aren’t up to par, especially on mobile.”. This is why we were giddy when he announced that Mobile Speed Score is now available in Google Ads.

How to Make User Acquisition Practically Free with Lambda School (Video + Transcript)


And when I started to take a step back and listen to the great product minds of this generation, I realized that they had all stumbled upon a few learnings that I had missed, and those were the learnings that allowed their companies to be successful.

Growth hacking was invented with a mint julep and two beers


I had to learn growth the hard way. We had to learn the hard way, by doing it ourselves. To learn this discipline in the past, you would have had to personally network your way to the top growth practitioners in Silicon Valley.

Security reflections and implications from Black Hat and DEF CON


Both include tons of practical and real world examples, learnings and live hacks and tests. Some of the key themes that were explored at Black Hat/Defcon this year were AI, Machine Learning, Blockchain, IoT and Election security.

The Decline of New SaaS Company Formation

Tom Tunguz

The promise of mobile remains only somewhat fulfilled. Machine learning in SaaS is nascent. The rate of new software company formation seems to have declined materially in the past few years. In 2011-2013, about 1450 software companies were founded each year on average. In 2014, that figure fell to 1186 and in 2015, we count 481. Why does Crunchbase data indicate this decline? First, there might be a few data issues in the most recent years.

5 Myths That Stop SaaS Companies from Moving Upmarket with Dropbox (Video + Transcript)


And so we learned two critical lessons at that stage. And the second part of it, the second lesson that we learned, was that you got to leverage the strength in one sales motion as you are going into the second sales motion. That’s something that we learned.

6 reasons to be bullish on SaaS

The Angel VC

5) Mobile expands the market to non-desk workers About ten years ago, the number of smartphone users was negligible. People in industries like construction, landscaping, hospitality and many other areas of “non-desk work”, who previously weren’t using any software, are now getting mobile apps that help them become more efficient.

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Gartner 2019 Magic Quadrant for Procure-to-Pay Suites (with Valuations)

Software Platform Consulting

AI/Machine Learning for guided buying or long-tail spend management. mobile-first. Gartner recently published its 2019 Magic Quadrant for Procure-to-Pay Suites. Once again , I have superimposed valuation information onto the Magic Quadrant. (I

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Has SaaS Become Commodified?

Tom Tunguz

Next-generation machine learning tools are also available by API and improving all the time. Mobile app distribution. A founder asked me if we had reached the point that SaaS is commodified. “Can you build a venture scale SaaS company anymore?” ” He made three key points to support the argument. First, the technology barriers to starting a SaaS company continue to fall.

Implications of Monoclouds for as-a-Service Startups - Why Differentiation Matters More than Ever

Tom Tunguz

Amazon released a mobile analytics product. This oligopoly on machine learning talent releases advances faster than any start up could. Plus with advances like Google’s TensorFlow Processing Unit, custom silicon for processing machine learning models, the incumbents’ advantage shows no signs of waning.

Subscription60: Monday, March 4th


As humans, we learn this in kindergarten, but as brands, we’re still trying to figure out how.". Some of the suggestions don't surprise us (Mobile is important? Let’s kick off the week, subscription fam. Abby here, wishing you a happy National Grammar Day.

Payments Industry Predictions for 2019


The growth of mobile wallet payments at POS systems – PayPal, Venmo, ApplePay, Amazon, ChasePay. Accelerated adoption of Machine Learning and AI among major financial institutions to fight fraud, increase automation, drive insights/offers, etc.

Why SKAGs Are No Longer a PPC Best Practice (and How to Respond)


Step into my time machine , and let us take a journey. But dedicated PPC managers took it in stride and learned to combat the change in other ways (e.g., What this indicates is that Google is gradually putting more faith in machine learning to understand human speech patterns.

Top 9 Takeaways from Fintech’s Money2020 Conference


Here are our team’s top 9 takeaways from the conference: Whereas the buzz last year was all about wallets , wallets, and wallets, most of the buzz this year was around AI, bots, and new mobile identity verification systems (haptic, biometric, and more). Machine learning is very important to an ever-increasing number of players in fintech. That said, machine learning success really depends on what data is available and how many predictive variables are created from the data.

Trends in Early Stage SaaS Fundraising Market of 2016

Tom Tunguz

These customers are hungry for novel software with similar user experiences to what they’ve become accustomed to on the web and their mobile phone. 17% of SaaS companies who have raised so far in 2016 employ machine learning. About $1B has been invested in early stage SaaS startups as of November 1. Over the last nine months, marketing startups have raised more dollars in aggregate than any other segment.

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The New UI for SaaS - The Question

Tom Tunguz

In many of these use cases, chats replace forms, the list of empty text boxes we must complete in order to accomplish almost anything on the Internet or mobile phone. Machine learning and large data sets enable this advance in user interface. Frequent use, because chat requires learning a new user interface, and behavior change demands repetition. Quick. Casual. Human. Chat differs from other forms of communication.