Is Machine Learning Overhyped?

Tom Tunguz

2016 was the year of machine learning. In this rare case, I think hype is masking quite a bit of true technical innovation. During last quarter of 2016, machine learning research has made huge strides. These innovations aren’t limited to the lab. 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.

Machine Learning in Consumer Products

Tom Tunguz

I believe machine learning will drive the next big wave of innovation in consumer web services. But ML and deep learning have reached a point that makes it harder and harder to pull back the curtain and expose weak technology.

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? I’ve written before about the monstrous acceleration in machine learning innovation. But a technology innovation alone is not enough.

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. Consequently, proprietary data sources that are essential to train next-generation machine learning models are easier to amass in enterprise rather than consumer. It’s not that we won’t see innovation in the consumer world.

Efficient Merchandising Using Machine Learning Algorithms

Backlinkfy

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.

The Innovations Free Compute and Storage Unleash

Tom Tunguz

The first manifestation of large scale, near-free compute I’ve seen is in machine learning. When I worked at Google in 2005, we would test individual machine learning models one or two at a time. Today, it’s possible for any company to test millions of machine learning models in parallel in minutes by distributing the work across tens, hundreds or thousands of machines with the push of a button.

A Technology Innovation Leading to a Go-To-Market Advantage

Tom Tunguz

The best way I’ve found to describe it is a technology innovation leading to a go-to-market advantage. RelateIQ machine learning to offer an innovative customer relationship management software to sales teams. Innovation = Invention + Go To Market. What do you look for in SaaS companies? It’s hard to answer this question concisely because there are so many different ways of building a great software business.

Why a Rapidly Changing World Requires Boards to Innovate and Bring Corporate Governance into the Digital Age

OpenView Labs

As directors, we’re charged with evaluating management on their ability to innovate and leverage emerging technology for competitive advantage, yet we rarely apply any of these standards to ourselves. Ask yourself: When was the last time your board innovated around its processes and procedures? Netflix’s Boardroom Innovation. While any innovation in the board world should be welcomed, the Netflix practices are unlikely to revolutionize corporate governance.

Five Reasons to Sell End-to-End Products in Early Markets

Tom Tunguz

In early and developing markets, selling complete products is often a superior go to market strategy, rather than selling an innovation in a layer in the stack. Second , in early markets, most of the buyers don’t understand the nuances of the technology, whether it’s IoT platforms, or machine learning infrastructures, or data lakes. Imagine you have just written machine learning model that prices stocks better than anything else in the market.

The Three Strategic Questions Facing AI Agencies

Tom Tunguz

Since writing The AI Agency: A Novel GTM for Machine Learning Startups , I’ve been meeting many companies who operate this way. These startups use machine learning to disrupt an industry traditionally dominated by agencies: law, accounting, recruiting, translation, debt collection, marketing…the list is long. In meeting many of these innovative businesses, I’ve observed they face three strategic questions.

AI 129

Totango Adds Personity.ai Team

Totango

With industry-leading enterprises confidently running on Totango’s Customer Success Platform, we are dedicated to innovating and bringing to market products that deliver Customer Success results. This acquisition allows Totango to extend its product leadership in enterprise Customer Success by delivering innovation faster to customers. Stay tuned for more information about all the exciting innovations to come. +.

Announcing our Investment in Chorus

Tom Tunguz

Advances in machine learning are transforming the software world. Two of the most exciting applications of machine learning are speech recognition and natural language processing. Chorus’ innovation suddenly unlocks all the insight stored in human conversation, an enormous data set that’s almost entirely unleveraged today.

The top SaaS companies ruling the East Coast

SaaStock

Bringing them together, we will help them and learn from them in equal measure. As a testimony to the quality of their service, Forter was recently again included in Forbes 50 “Most Innovative Fintech Companies In 2019” list.

When Will the Next Wave of UI Advances Happen?

Tom Tunguz

Technology innovations swing to a pendulum’s cadence. Sometimes innovations begin with infrastructure changes and reverberate up the stack. Other times, front-end engineers innovate at the application layer, which demand downstream changes in the infrastructure to scale. One could argue there have been innovations at the platform tier. New machine-learning APIs transcribe speech, categorize text, recognize images, translate words, and predict.

An Announcement from the CEO: Unveiling Cortex + ReSci

ReSci

We pride ourselves on emphasizing substance over being shiny, and we’ve invested heavily in data science and machine learning to develop a product that brings true value to our partners. Continued innovation has always been a. At Retention Science, we’ve always been a technology-first company.

Join us for Customer Success Summit 2018!

Totango

We’re going to bring the best and the brightest from the field to share latest trends in strategy and innovation so you and your organization can make the BIGGEST IMPACT possible in customer adoption, retention and overall customer engagement. You should attend CSSummit18 if you want to learn how to : Adopt Customer Success methodologies across all types of industries and verticals including non-SaaS organizations, and how to make a greater impact on your customers. .

Totango Welcomes personity.ai to the Team

Totango

With industry-leading enterprises confidently running on Totango’s Customer Success Platform, we are dedicated to innovating and bringing to market products that deliver Customer Success results. This acquisition allows Totango to extend its product leadership in enterprise Customer Success by delivering innovation faster to customers. Stay tuned for more information about all the exciting innovations to come. +.

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

TechStars

The 13-week mentorship-driven accelerator program will work with the following 10 startups driving innovation in the next-generation of financial services solutions and payment technology.

AI 50

Top Global SaaS Trends You Should Know with Google Cloud and Zenoss (Video + Transcript)

SaaStr

As a global technology provider powering thousands of SaaS companies, Google is at the forefront of driving exciting and innovative technologies to market. You’ll also learn how leading SaaS companies are able to scale and thrive in this complex, dynamic environment.

Trends 186

The Promise of Global Digital Identities: Facilitating Ecommerce In A World Where Everyone Is A Merchant

wepay

Machine learning and artificial intelligence are all the rage and, to a certain extent, how we techies have differentiated ourselves from traditional financial institutions. WePay employs machine learning models trained to distinguish between fraudulent users and good ones.

7 Predictions for SaaS in 2018

Tom Tunguz

Machine learning fades as a buzzword. ” Just as those trends have become ubiquitous to be implicit, so will machine learning. Founders will look to apply the innovation of a distributed and decentralized-trust database in different parts of the ecosystem. Below are 7 predictions about the startup software ecosystem. How many of them do you agree with?

Adoption Chain Risk - The Importance of Selling to Everyone in Your Startup's Supply Chain

Tom Tunguz

In the Wide Lens , Dartmouth Entrepreneurship professor Ron Adner explores the risks associated with innovation. Then there’s co-innovation risk, what might be called chained technology risk. Adoption Chain Risk is “the extent to which partners will need to adopt your innovation before end consumers have a chance to assess the full value proposition.” ” Adoption Chain Risk applies the idea of a supply chain to innovation.

The SaaS superstars of the East Coast

SaaStock

Bringing them together, we will help them and learn from them in equal measure. As a testimony to the quality of their service, Forter was recently again included in Forbes 50 “Most Innovative Fintech Companies In 2019” list.

All New Ideas are Combinations of Old Ideas

Tom Tunguz

Johannsen argues in his book that most innovation comes at the intersection of fields, and Pearson is just one example. In 2005, an economist named Benjamin Jones published a paper called The Burden of Knowledge and the ‘Death of the Renaissance Man’: Is Innovation Getting Harder? Even PhDs who spend 5 to 6 years researching a particular field like machine learning specialize in a niche and will not be experts in just the field of ML.

Join us for Customer Success Summit 2018!

Totango

We’re going to bring the best and the brightest from the field to share latest trends in strategy and innovation so you and your organization can make the BIGGEST IMPACT possible in customer adoption, retention and overall customer engagement. You should attend CSSummit18 if you want to learn how to : Adopt Customer Success methodologies across all types of industries and verticals including non-SaaS organizations, and how to make a greater impact on your customers. .

Wootric’s Deepa Subramanian on measuring the voice of the customer

Inside Intercom

Deepa joined me for a chat about everything from ways to prioritize customer experience to going all-in on machine learning. When building machine learning , large generic training models aren’t always the best. Lessons on building machine learning.

My Algorithm is Better than Yours

Tom Tunguz

They aren’t technology innovations leading to a go-to-market advantage. I first observed the use of large scale machine learning at Google. My algorithm is better than yours. My algorithm performs better on the precision/recall tradeoffs. It surfaces fewer false positives. It converges to an answer faster. Perhaps it requires a bit less data. Those statements might all be true. But none of these advantages confer a competitive sales advantage in the market.

We Haven’t Hit Peak SaaS

Hitenism

Innovate on the Business Model. You have to flirt with new technologies like machine learning to see how they might apply to your business.

6 reasons to be bullish on SaaS

The Angel VC

The next wave of enterprise software will likely be powered by machine learning (check out this TechCrunch post for a good primer) and continued consumerization ( and in some cases, new hardware ). These and other innovations will allow SaaS applications to get even wider adoption and to provide even more value to its customers.

Cloud 149

Beyond $1B ARR: Lessons from Zendesk on Why the Cloud is Unstoppable (Video + Transcript)

SaaStr

All these new generation of services and we work with these type of companies all over the world and we have learned so much from them. What kind of customer experience, what kind of innovation do we need to help do you gather? And all the innovation has been done.”

Cloud 244

The Rising Stakes in SaaS

Tom Tunguz

Machine learning, broad consolidation, category creation, and new distribution models each will change the SaaS ecosystem in fundamental ways. As the number of new startups ebbs, and major forces in the industry reshape it, I suspect we’re going to see a massive amount of innovation in SaaS, a reinvention after the perfection of a 20 year old playbook Last week, I participated in two discussions about the changes in the SaaS world. I believe they are fundamental.

Salesforce’s Mike Kreaden on how to build a platform to drive growth

Inside Intercom

Machine learning can get the right message or recommendation out in a responsive way – not just from the customer’s next best action, but from the sales perspective, too. Salesforce AppExchange: Celebrating 10 Years of Innovation and Growth from Salesforce.

Payments Industry Predictions for 2019

wepay

Accelerated adoption of Machine Learning and AI among major financial institutions to fight fraud, increase automation, drive insights/offers, etc. Innovation (open APIs, frictionless checkout, improvements in payment security) and standardization in the form of PSD2, 3DS2.0,

People of WePay: Vinodh Poyyapakkam, Vice President of Risk Management

wepay

In order to do that we use advanced machine learning techniques as well as an expert human risk team that combine to deliver best-in-class protections. What’s a lesson we’ve learned in dealing with risk and how do we act on it?

Startup Best Practices 24 - Marketing Your Product with Novel Framing to Maximize Sales Success

Tom Tunguz

Machine learning. Novel language, challenger sales, innovative product is a powerful combination Every software company competes with another — if not directly, then at least for budget. With global IT spending flat to down in 2015 and 2016 , software businesses are fighting for share of wallet. At this point, the critical marketing imperative is to start a conversation with a receptive buyer, and do it thousands of times per year. But how?

Top 9 Takeaways from Fintech’s Money2020 Conference

wepay

It was a great time connecting with innovative people and companies that geek out on payments like we do, and participating in a bunch of thoughtful discussions regarding what’s next at the intersection of financial services and technology. 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

Meaningful innovation will be required to shift customers once more. 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. The chart above shows the early-stage investment dollars by buyer within the organization.

Trends 100

riskmethods Receives an Additional 13.5 Million Euro Growth Capital

The SaaS Garage

Using AI, machine-learning algorithms and Big Data, riskmethods helps its customers avoid revenue loss, loss of production, and reputational damage linked to supply chain issues at a time when progressive globalization, relocation to new markets, national and international regulations, and political unrest are increasing the risks along the supply chain. Bayern Kapital has invested over 246 million euros equity in around more than 250 innovative technology-oriented companies.

Key strategies to successfully scale your customer support

Inside Intercom

It’s an age old question for anyone leading a customer support organization, the sort of challenge that requires continuous innovation as a company and its customer base expands.

Best 150+ Sales Tools: The Complete List (2019 Update)

Sales Hacker

By combining cloud technology, machine learning and data science, Aviso takes human insight into the next actionable level. Bring the power of data science and machine learning into your workflow. RO Innovation. It takes a lot to succeed in sales.

Sales 111

State of the Cloud 2019 from Bessemer Venture Partners (Video + Transcript)

SaaStr

And you get folks like Tobi at Shopify and also this room, I’d like to think, are now part of this club that’s driving tech innovation and tech value creation and job creation on a massive massive scale. And so, what is the lesson learned for us today?

Cloud 213

The New UI for SaaS - The Question

Tom Tunguz

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. There’s a wave of innovation looming with chat user interfaces powered by artificial intelligence (with human fallback), and we’re just at the start of it Quick. Casual. Human. Chat differs from other forms of communication.

SaaStr Podcast #227: Alexandr Wang, Founder & CEO @ Scale On Why TAM In The Traditional Sense Barely Matters

SaaStr

I went back to MIT, was doing machine learning research and then I sort of got antsy. And then I think the Henry Ford quote is great and all and that’s really how you get discontinuous innovation and whatnot but usually on the product side, you have a couple big bets.