Here Are More Details on Salesforce’s Plan to Smarten Up Sales and Marketing Software

by
Barb Darrow

@FortuneMagazine

September 18, 2016, 6:21 PM EDT

Salesforce, which has been dribbling out details of its grand plan to add artificial intelligence to its sales-and-marketing software for weeks, did a bigger reveal Sunday, a few weeks before its Dreamforce event and—not coincidentally—just as rival Oracle kicked off its annual Oracle OpenWorld tech conference. The timing is probably not a coincidence.

Basically, Salesforce crm is adding more intelligence to each of its branded Marketing, Sales, Service, Commerce, and App clouds, with a mix of AI technologies built in-house and acquired in a series of acquisitions, including of RelateIQ in 2014 and Metamind last April. Salesforce Einstein, as the effort is known, seeks to help Salesforce customers wring real value out of the tons of data they generate.

Is there a major client that you haven’t heard from in awhile or who has been name-dropping your competitor in email or or on social media? It’s time to reach out. Do you want to see if your branding is getting out there? Why not pull every mention or relevant photo posted on Facebook or Twitter twtr or other social network? That’s some of what what baked-in AI makes possible.

Get Data Sheet, Fortune’s technology newsletter.

If you have hundreds or thousands of sales prospects on a list, how do you tell the potential winners from the duds? Salesforce says its Marketing Cloud’s Predictive Scoring will prioritize which prospects are most likely to actually write a check over the tire kickers.

“Every sales person wants to sell more, they want more qualified leads, not window shoppers,” Richard Socher, chief scientist at Salesforce, told Fortune. “We combine CRM information with e-mail and calendar data. We can detect if a competitor is mentioned on an email thread.”

Not only that, the software can do a better job tracking responses (or lack thereof) to marketing pitches, he said. “Machine learning will flag us if a C-level person is not responding.”

Salesforce started down this path a few years ago and is using a combination of in-house and acquired expertise to build AI for CRM, according to John Ball[, senior vice president and general manager of Salesforce Einstein.

Even before the flurry of acquisitions, Salesforce was working on some of its own AI projects and fielded a multi-tenant platform capable of running this technology. But Salesforce also identified specific technologies for acquisition, he added. On Salesforce’s most recent earnings call chief executive Marc Benioff boasted of the team of the 175 data scientists the company now has on staff.

AI, and the whole idea of helping companies derive actual financial benefits from their data, is a big push for nearly every tech company. Amazon amzn , IBM ibm (with its ubiquitous Watson), Microsoft msft and Google goog are all pouring resources into making their own software smarter and able to automate tedious tasks formerly performed by humans.

Salesforce says it can apply AI technologies like machine learning, to sort through an ocean of available data —from email, chat, social networks, traditional databases—and prioritize it for its customers, in this case sales people, marketers, and service personnel.

For more on Salesforce read 5 Things to Know from Salesforce earnings call.

“We have tons of data on our accounts, opportunities, communications around email and calendar and interaction data like campaign emails and social data from Social Studio, Community Cloud and Chatter,” said Socher, who was formerly chief executive of MetaMind. “Einstein uses deep learning, machine learning and natural language processing to those rich signals. With that we can surface predictions in the context of the business user.”

Salesforce Community Cloud lets partners and customers share information. Chatter is a Slack-like messaging service for employees, and Social Studio lets customers keep an eye on social media commentary about their companies.

For more on Marc Benioff watch:

Each piece does its part. RelateIQ, for example, continuously evaluates incoming data about salesperson-client interaction and, if it notes a lack of communication/feedback in a set amount of time, recommends a call or other outreach. Sources said after Salesforce bought this company two years ago, Benioff wanted to affix “IQ” to each of the company’s clouds, but the advent of IBM Watson and the marketing hype it’s generated, caused him to switch to Einstein. So what would hav been the MarketingIQ cloud is now the Marketing Einstein cloud.

Meanwhile, MetaMind, combines natural language processing, computer vision, and database predictions in a way that will let marketers search for data relative to any topic. If that topic happens to be soccer, it can search across social media not only based on language and relevant company names, but on images. That way it can distinguish between posts about soccer (aka football in most of the world) and American football since the software can differentiate between a round soccer ball, and the more elliptical American football.

The new AI capabilities will run both in Salesforce’s own data centers and on its products that also run on Amazon Web Services, Ball said. Last May, Salesforce said it inked a deal to use AWS infrastructure to run a bunch of its new software.

A lot of Einstein roll-out details are still to come. Some of Salesforce’s new AI features will be blended into existing cloud offerings at no additional charge. Others will carry an additional cost. Many of the promised capabilities won’t launch till next year.

The predictive scoring for marketers as described above will be available in October, as will a “predictive audience” feature that claims to forecast likely behavior of a given audience segment based on current data. Both will be part of the marketing cloud. Also available in October will be a product recommendation feature for the Commerce Cloud that will tailor product recommendations for shoppers based on their mobile, desktop, and in-store interactions. Salesforce Commerce Cloud is basically Deamndware, the e-commerce company Salesforce bought for $2.8 billion in June,

Both Socher and Ball repeatedly noted that AI from all these sources will be tightly integrated into the company’s core clouds soon. Still, given that many of the relevant companies—including Demandware, MetaMind, Implisit, and TempoAI—were acquired within the last year, it’s hard to see just how deep that integration can be. Customers will be able to judge for themselves next year when more of the capabilities come online.

How Data And Machine Learning Are Changing The Solar Industry

by
Barb Darrow

@FortuneMagazine

September 14, 2016, 10:44 AM EDT

Like most sectors, the solar industry is rapidly embracing ways to analyze and crunch data in order to lower the cost of solar energy and to open up new markets for their technology.

The rise of data tools—algorithms, machine learning, sensors—are driving investments in, and acquisitions of, solar startups, while entrepreneurs are launching new companies that are using data to solve various solar industry problems. Meanwhile, big companies are spending money on tracking, monitoring and evaluating data from solar projects worldwide, helping to lower the cost of generating energy from the sun.

It shouldn’t come as a surprise that the solar sector is the latest to embrace the value of data. Other traditionally non-digital sectors, like the auto industry, oil and gas, and agriculture are turning to managing data as a necessity to keep their technology competitive and their companies in business.

But when it comes to the solar industry, it could end up being data that ultimately pushes down the cost of solar enough so that it can compete with fossil fuel energy. In that way, it’s not just a way for solar companies to make money (though it’s that, too), but it would also be a way to transition the world from generating energy that emits tons of planet-warming carbon emissions.

For more on why solar energy is more affordable than ever watch our video.

At a solar industry conference in Las Vegas this week, companies across the solar industry are talking about their latest data technology and plans.

On Wednesday, a young startup called PowerScout, based in Oakland, Calif., announced that it has raised a seed round of $5.2 million to expand its technology that uses big data, analytics, and e-commerce to find smarter ways to sell solar panels to consumers. The company’s software amasses tons of data on current and potential solar customers, and uses machine learning to predict which of them are likely to buy solar panels.

Machine learning is an artificial intelligence technique that involves feeding data to algorithms so that the machine learning-powered algorithms get better at figuring our patterns in the data. Turns out it can be helpful for selling solar panels.

Selling solar panels to consumers has emerged as a tricky and expensive problem for companies. Particularly, as some markets, like in California, have been successful enough that many of the early adopters already have solar. That means in those places, increasingly, solar companies will have to convince more mainstream customers, who are generally more price-sensitive, to buy solar panels.

PowerScout CEO Attila Toth tells Fortune from the conference in Las Vegas that solar is “still being sold door-to-door just like vacuum cleaners in the 1950s.” That means consumers end up paying more, because of the high costs of the sales process itself, instead of just for the panels.

The company, whose funding includes millions of dollars from the Department of Energy, has also partnered with Google’s GOOG Project Sunroof, which is using data to build similar solar software.

Get Data Sheet, Fortune’s technology newsletter.

Other startups are using data to make it easier to finance the cost of installing solar. Last week a San Francisco-based company, kWh Analytics, introduced a new solar software product that uses data from global solar projects to convince insurance companies to back a production guarantee for solar projects. The guarantee drives down the interest rate for money raised for solar systems, and thus lowers the cost of financing them.

Solar data has historically “been fairly disorganized,” and the industry has little information about who builds quality solar projects, says kWh Analytics CEO Richard Matsui. The company counts Google, which has bought over 2.5 gigawatts over clean energy, as a client. This summer kWh Analytics raised a $5 million round of funding from Anthemis Group and power giant Engie.

Solar data startups aren’t just launching and raising funds from venture capitalists. Big companies are buying them, too.

Last month electronics giant Flex, through its solar gear subsidiary NEXTracker, revealed that it had bought a machine learning startup called BrightBox Technologies. The three-year-old company, based in Berkeley, Calif., developed software to optimize heating and cooling systems in buildings.

PowerScout uses tons of data to predict who's the next million solar customers. — PowerScout uses tons of data to predict who’s the next million solar customers.

But NEXTracker plans to use the company’s software—and the co-founders’ brainpower—to use machine learning to optimize the development and operation of its solar hardware globally. Smarter monitoring and maintenance of solar panels, as well as the gear for moving the solar panels, can help lower costs by optimizing solar production.

Even machine learning giants, like IBM IBM , are developing ways to use data to make solar energy cheaper. In 2013, IBM’s research division, using Department of Energy funding, started working on figuring out how to leverage artificial intelligent engine Watson for clean power.

Today IBM Research has 200 partners that use its solar and wind forecasting technology, which can predict solar and wind conditions from between 15 minutes to 30 days in advance. The tech was built by blending dozens of forecasting models and adding in tons of data about weather, the environment, atmospheric conditions, and how solar plants and the power grid operate. The engine also trained on environmental data collected from 1,600 sites around the U.S.

The result is that IBM’s “self-learning weather model and renewable forecasting technology” (formerly called Watt-sun) is 50% more accurate than the next best solar forecasting model, says project manager Hendrik Hamann. IBM is looking into ways to commercialize the technology, following its birth in the research division.

Data sources on display in IBM labs used in IBM's solar forecasting technology. — Data sources on display in IBM labs used in IBM’s solar forecasting technology.

Even in off-grid markets in sub-Saharan Africa, ultra low cost solar is benefiting from machine learning. A British startup called Azuri, which sells solar panels and batteries that are managed with cell phone tech, is using machine learning to learn its customers usage patterns and to manage the batteries and power sources in the most optimal way. For example, if a customer’s battery starts to get low, the system automatically adjusts the brightness of the lights and slows the rate of cell phone charging as to make the energy last as long as possible.

Solar panel and project developer SunPower SPWR says it’s accumulated more operational data about solar panel power plants than any other company in the industry. SunPower says it uses this data to improve panel technology, customer service, and how SunPower sites, builds, and operates projects. SunPower also has a control center in Austin that will be able to monitor and manage more than 1.8 gigawatts of solar panel projects by the end of the year.

It’s not one specific data tool that is rocking the solar industry. It’ll be a combination of many ways that data can reduce the cost of solar that will prove crucial to transforming solar into a more mainstream energy source.

Solar panels are already at their cheapest point in history. It’s now up to software and data to make sure those low cost solar panels are able to get into big solar farms and onto rooftops as quickly and easily as possible.

IBM Names First-Ever Chief Marketing Officer

by
Barb Darrow

@FortuneMagazine

September 13, 2016, 1:44 PM EDT

IBM’s first chief marketing officer is Michelle Peluso, the former chief executive of flash-sale site Gilt, now part of the Hudson Bay Company.

The company formerly had senior leaders of its marketing efforts, but the CMO title is new. Peluso will report to Jon Iwata, IBM’s senior vice president for marketing and communications.

Peluso is “the ideal leader to accelerate and build on” IBM’s efforts to transform itself and its marketing, Iwata says.

She was most recently a venture partner at Technology Crossover Ventures, which she joined last May. But she has marketing experience from an earlier stint as Citigroup’s global consumer chief marketing and Internet officer.

Peluso’s Gilt pedigree indicates a consumer focus, which may come in handy as IBM ibm seeks to put a consumer-friendly face on business applications of all kinds.

It also comes as IBM is pushing Watson, its artificial intelligence star technology, as a way to ease virtually all modern jobs from medical research to shopping.

Get Data Sheet, Fortune’s daily technology newsletter.

Over the past few years or so, the role of chief marketing officer has evolved and grown considerably. Once seen as the people in charge of brochures and email campaigns, chief marketers are now getting considerable budget to get things done faster, without having to go through traditional IT channels.

That means they have more money to spend on tech services, in particular for things like customer relationship management or sales tracking software. The feeling has been that traditional IT departments were too slow moving to help companies that need to be fast on their feet to survive.

For more on IBM, read: IBM Vows Transparency on Financial Reporting, With One Big Exception

So why is IBM creating the chief marketing officer role now, at the ripe old age of 105? According to a company statement, the move signals the “transformation of marketing—investing in digital skills, using data to deeply understand clients … and building consumer-grade experiences.”

For more on Watson, watch:

IBM is no slouch when it comes to marketing. Its campaigns around Watson, for example, are the envy of competitors. Steve Gold is the chief marketing officer for the Watson business unit, so while there was no corporate CMO up till now, there have been people who carry the title at the business group level.

Salesforce Will Drop More Einstein Details Before Oracle Event

by
Barb Darrow

@FortuneMagazine

September 1, 2016, 5:11 PM EDT

Salesforce will share more information about its hyped-yet-still-secret artificial intelligence technology before its annual Dreamforce conference in October. In fact, it will start talking publicly about its Einstein AI effort in two weeks, which is, coincidentally or not, just before Oracle’s orcl annual conference kicks off.

On the Salesforce earnings call Wednesday, chief executive Marc Benioff talked up “Einstein” in very general but extremely glowing terms. He had already disclosed the product name and some details to Forbes last week. Benioff, after all, is a master of parceling out snippets of information to keep the headlines fresh—and focused on Salesforce crm . And so here we are.

By putting the news out in mid-September, instead of at Dreamforce, which starts a few weeks later, Benioff does two things. One: He keeps drumming up interest among Dreamforce attendees. Two: He steals the spotlight from Oracle OpenWorld, which kicks off Sept. 18 in San Francisco.

Benioff and Oracle executive chairman Larry Ellison are frenemies of the first order. Benioff started his career at Oracle 30 years ago and was a top lieutenant to Ellison, whom he calls a friend and mentor. But the two do enjoy a good tussle every once in a while. They tangle about which company’s tech conference is bigger. About which offers the best online software. About which represents “true” cloud. You get the drift.

Five years ago, Benioff was once bounced from his OpenWorld keynote, and worked that into a media goldmine.

Now Benioff is all about Einstein and artificial intelligence. Basically that is software that teaches itself new skills based on the data it’s parsed and interactions it’s had. Imagine a program that knows what you want even before you ask based on its past interactions with you and your colleagues. That could be interesting.

To be fair, although Salesforce has bought AI companies including RelateIQ two years ago, MetaMind, Implisit, PreductionIO, and TempoAI, it is a bit late to this party. IBM ibm , after all, has been dining out—at least in PR terms—on Watson ever since Watson kicked Ken Jennings’ butt on Jeopardy five years ago.

“After buying RelateIQ, Benioff was going to call everything ‘blank IQ,’ but when he saw the traction IBM was getting with Watson, he wanted something else, and Einstein was born,” said one source close to Salesforce who insisted on anonymity.

Get Data Sheet, Fortune’s daily newsletter on the business of technology.

On the earnings call on Wednesday, Benioff said Salesforce would offer AI-enabled versions of all of its existing software products that are widely used by sales and marketing people in big companies.

Thus there will be a Sales Cloud Einstein, a Service Cloud Einstein, a Marketing Cloud Einstein, and an Analytics Cloud Einstein. And corporate software developers would be able to build their own AI features using “Einstein extensions and Heroku,” Benioff noted. Heroku is a software development platform Salesforce acquired five years ago.

For more on Marc Benioff watch:

And he also noted Einstein would suit both techies who know how to program and mere mortals in sales and marketing departments who just want smarter software that may anticipate their needs. These are some mighty big promises, as is the contention Benioff made that the company has managed to take all those acquired companies and their technologies and “stitch” them together.

Given that integrating technologies from so many companies is a complex and tricky process, it will be interesting to see how Einstein turns out.

IBM Revives Its Fight With Intel Over Server Chip Dominance

by
Barb Darrow

@FortuneMagazine

August 23, 2016, 6:38 PM EDT

Intel remains at the top of the heap of server chip makers, but that doesn’t mean rival f500link]IBM[/f500link] has given up.

Quite the contrary, IBM ibm this week renewed its push to make its Power9 chip a top contender. It revealed specifications for the new “P9” chips Tuesday at the HotChips technology conference in Cupertino, Calif.

Starting next year, P9- based systems will be available from IBM and associated hardware partners, according to an IBM spokesman.

The chips will go into servers starting for as little as $6,000, but the purported beauty of these new chips is that they will act as expandable hubs into which server makers can plug graphics chips as well as special-purpose Application Specific Integrated Circuits (ASICs) and other performance enhancers as needed.

That means manufacturers can fine-tune the boxes they make for specific purposes to, in theory, wring the best performance out of the hardware. So, if you want to sell a server that runs a small number of real-time algorithms very fast, you can do so.

The Power9 chip will come in two basic designs, one for crunching numbers for big data or artificial intelligence applications like IBM’s favorite product Watson. The second will target Google-like “hyperscale” applications that must run across hundreds or thousands machines.

Matt Eastwood, senior vice president at research firm IDC says IBM has a shot at upsetting the status quo since lots of IT workloads are shifting due to the trend toward cloud computing, where more companies are using third party cloud providers instead of building more of their own data centers, the preference for mobile devices over desktop and laptop PCs, and the Internet of things, which requires the connection to and processing of data from billions of devices.

“Three areas of focus for IBM will determine its ultimate success, demand in China, success with the big tier 1 cloud service providers, and its ability to grow its hardware and software ecosystem,” he noted

This is an interesting story for IBM. Given Intel’s intc dominance, IBM’s chip architecture was pretty much used by IBM alone until three years ago, when the company decided to make its Power software and hardware technology available to outsiders via the OpenPower Foundation.

Initial partners in the foundation included Mellanox mlnx which makes switches and host adapters; NVIDIA nvda , which makes graphics processors; and Tyan, which produces motherboards. Those are all key server components, but the biggest brand coming aboard was Google goog , which said it was interested in using POWER chips in its own servers. That was definitely a coup for IBM because Google uses hundreds of thousands or millions of servers to power its Internet search, cloud computing, and other businesses.

For more on IBM, watch:

Since that time Google, which can be secretive about what technology it uses internally, has reportedly run earlier Power8 chips in its servers. And Google data center guru Urs Hölzle told technology trade publication The Next Platform that the company would run Power9 if it could realize a 20% power savings.

Words like that have got to get Intel’s attention.

Get Data Sheet, Fortune’s technology newsletter.

IBM and AMD amd are banking that the big hyperscale players that run massive data centers worldwide—Google, Amazon amzn Web Services, Facebook fb , and Microsoft @msft msft — want a strong alternative chip source. AMD has been pushing its “Zen” server processor technology which chief executive Lisa Su recently told Fortune is taking off.

This story was updated with analyst comment and more context about the competitive landscape.

Why Intel Bought Artificial Intelligence Startup Nervana Systems

by
Barb Darrow

@FortuneMagazine

August 9, 2016, 4:09 PM EDT

Intel is bolstering its artificial intelligence efforts by acquiring Nervana Systems, a two-year-old startup considered among the leaders in developing machine learning technology.

Nervana has built an extensive machine learning system, which runs the gamut from an open-sourced software platform all the way down to an upcoming customized computer chip. The platform is used for everything from analyzing seismic data to find promising places to drill for oil to looking at plant genomes in search of new hybrids.

Intel intc declined to disclose the purchase price for the deal, which is expected to close in about one month.

After transitioning from mainframes to PCs to servers to cloud-based data centers, computing is about to make another transition, says Intel vice president Jason Waxman, who runs the data center solutions group. “Right now, we’re on the precipice of the next big wave, artificial intelligence,” he tells Fortune. “We’re already seeing real deployments.”

Get Data Sheet, Fortune’s technology newsletter.

Most of Intel’s efforts so far have focused on adapting its popular line of Xeon general purpose computing chips for use in machine learning and artificial intelligence deployments. Last year, it released a specialized version of the chip, dubbed the Xeon Phi, which had more cores for more processing in parallel. That’s intended to beat out graphics chips from Nvidia nvda and others that also have large-scale parallel processing capabilities.

Nervana brings expertise on the software side that can be used right away as well as designs for specialized chips that can be accelerated with Intel’s chipmaking know-how.

The startup’s chip design “slots in perfectly with this Intel acquisition,” says CEO Naveen Rao, who worked on developing neural networks inspired by biological brains at Qualcomm qcom before co-founding Nervana in 2014. Customers will be able to try the first Nervana chip designs early next year, he says.

Nervana’s platform had been running on Nvidia chips previously. Rao says that was to get to market quickly with its software before the customized chips were ready.

A higher rate of data flow will be among the key differences between the upcoming specialized chips and the general purpose and both the graphics chips widely in use today.

Machine learning systems work more like a brain, which has billions of neurons each linked to thousands of synapses all working in parallel. The systems need to read and write data from storage, sharing that data internally among chips very quickly in order to mimic the parallel operation of the neurons and synapses.

The new Nervana chips will be able to transfer data in and out at 2.4 terabytes per second, and with very low latency at a rate five to 10 times faster than the fastest input-output interfaces for traditional chips, Rao says.

For more on the future of AI, watch:

Initially, the new chips will be aimed at cloud data centers, where big companies are making extensive use of machine learning, Intel’s Waxman says. But eventually the technology will wind its way into smart devices such as self-driving cars and wearables to fuel the growth of the Internet of things, he says.

Still, there’s plenty of competition in the race to offer the fastest and most efficient machine learning platform. The field ranges from from giants like IBM ibm , with its Watson effort, and Google’s goog DeepMind to startups like Osaro and Skymind. Intel is hoping its acquisition of Nervana will help it lead the way.

These New Google AI Tools May Help Newbies Build Smarter Software

by
Barb Darrow

@FortuneMagazine

July 20, 2016, 1:09 PM EDT

Google is debuting two new tools that businesses can use to bring natural language capabilities to computer systems.

The tools help with machine learning, a subset of artificial intelligence (AI) that involves computers recognizing patterns in data to teach themselves new behavior. Based on lots of data acquired over many interactions, a program may learn that when a person raises her voice (or types in all caps) it may be best to prompt the user in one way versus another, for example.

Google goog is now offering developers early versions of its Cloud Natural Language API to help computers understand the written word and Speech API for doing same with the spoken word.. Application programming interfaces are an important element in developing software that let different computer programs to communicate with each other and share information.

“We are exposing the APIs directly to end customers so they can build their own models to do what they want to do,” Rob Craft, group product manager for cloud machine learning, told Fortune in advance of the news.

He said this is part of Google’s attempt to spread machine learning beyond the ivory tower of researchers and computer cognoscenti.

“There are lots of use cases, supermarkets can use this, it’s not just the for the 1% investment IT shops,” he said.

Computers can’t read your mind yet, but they’re getting closer

As an example, Craft cited how the U.K.’s Ocado online supermarket is using the the newAPIs to figure out what its customers are most happy or upset about based on their email or texts to the store.

“Doesn’t it make sense to route the most upset customer to the most trained customer service agent?” he said. Using the natural language API, Ocado can use computers to scan, parse, and try to understand what customers are saying and then triage the messages.

“You can get analysis on the subject, what it’s about, and also the sentiment. Are they mad? Happy? Somewhere in the middle?”

“We have pretty good intelligence around swear words,” he added. The initial API can translate English, Spanish, and Japanese.

Get Data Sheet, Fortune’s technology newsletter.

In November, Google made its Tensorflow machine language software available to anyone who wanted to work with it. Google, which used Tensorflow internally to build machine learning into some of its consumer products, created these machine learning APIs based on the models it created in the process.

Check out Google cloud chief Diane Greene’s talk at Fortune’s Brainstorm Tech:

For example, a spokeswoman explained, the Speech API is based on models used in Google Now the company’s Apple aapl Siri-like personal assistant , and the Cloud Natural Language API is based on models used in Google Search and Parsey McParseface research, which helps computers learn grammar.

Machine learning, and AI more broadly, represents a big battleground for tech companies, all of which are striving to build smarter, more independent computer systems like IBM ibm has done with Watson; Microsoft msft with Skype translator and other services, and Amazon @amzn amzn Web Services machine learning and other services.

Here’s Your Complete Guide to Fortune Brainstorm Tech 2016

by
Barb Darrow

@FortuneMagazine

July 14, 2016, 4:02 PM EDT

Fortune’s annual technology conference, Brainstorm Tech, is a forum for fascinating discussions by some of the industry’s top leaders, thinkers, and innovators.

If you missed this year’s event, which was held from July 11 to 13 in Aspen, Colo., you can catch up easily using our handy guide below. It’s a compilation of all of the event’s coverage by Fortune staff. Enjoy.

CONNECTING THE CAR: THE ROAD AHEAD
With General Motors president Dan Ammann and Lyft co-founder and president John Zimmer.
Moderated by Fortune’s Adam Lashinsky.

—Article: Lyft President Says the Company Has More Than Enough Money to Break Even, by Erin Griffith
—Article: How General Motors Expects Self-Driving Cars to Become a Reality, by Erin Griffith
—Video: General Motors Is Very Happy With its Lyft Partnership
—Video: Lyft Prefers to Think It’s Investing Money—Not Losing it
—Video: Lyft Is Partnering With Uber’s Global Competitors

TILTING THE SCALE ON CLOUD COMPUTING
With Google senior vice president Diane Greene and Fortune’s Andrew Nusca.

—Article: It’s Google’s Time to Shine in Big Business, by Barb Darrow
—Video: How Google Is Tackling Healthcare, Financial Services, and Media
—Video: Google ‘Gets’ Big Business
—Video of the entire session

WHAT MAKES A LARGE PRIVATE COMPANY TICK?
With Koch Industries chairman and CEO Charles Koch and Fortune’s Alan Murray.

—Video: Is Government Policy Too Restrictive For Big Business?
—Video: How Koch Industries Challenges Its Employees To Be Innovators
—Video: Why Koch Industries Isn’t Supporting a Presidential Candidate
—Transcript of the entire session
—Video of the entire session

CAN GOVERNMENT DISRUPT ITSELF?
With U.S. Digital Service co-founder Haley Van Dyck and Fortune’s Leena Rao.

—Article: Uncle Sam Wants You to Join This Digital Startup, by Robert Hackett
—Video: Can Government Disrupt itself?

CONTEMPLATING ARTIFICIAL INTELLIGENCE
With IBM Watson’s David Kenny, Humatics’ David Mindell, Bloomberg Beta’s Shivon Zilis, and Fortune’s Adam Lashinsky.

—Article: Data Is the New Oil, by Jonathan Vanian
—Video: Data Is the New Oil
—Video of the entire session

WHAT’S THE BIG DEAL?
With Microsoft’s Peggy Johnson, GV’s Bill Maris, TPG’s David Trujillo, and Fortune’s Dan Primack.

—Article: Why Blood Test Startup Theranos Raised Money So Easily, by Kia Kokalitcheva
—Video: The Ripple Effect of Theranos In Biotech Investing

SYNCING UP WITH DROPBOX
With Dropbox’s Drew Houston and Dennis Woodside and Fortune’s Dan Primack.

—Article: Dropbox Says Controlling its Own Tech Makes it Faster, Nimbler, by Barb Darrow
—Video: Synching up with dropbox

A NEW WAY TO WORK
With WeWork’s Adam and Rebekah Neumann and Fortune’s Andrew Nusca.

—Article: WeWork Is Not Afraid to go Public, by Erin Griffith
—Video: Will WeWork IPO?
—Video of the entire session

KEYNOTE CONVERSATION
With Disney chairman and CEO Robert Iger and Fortune’s Michal Lev-Ram.

—Article: The Best Protection Against Disruption Is a Great Story, Says Disney’s CEO, by Mathew Ingram
—Video: Disney’s Bob Iger Discusses the Future of Interactive Storytelling
—Video: Disney CEO Bob Iger Talks About Creating Future Entertainment, Today
—Video: Disney’s Bob Iger Isn’t Worried About Losing ESPN Subscribers
—Video of the entire session

HALT AND CATCH FIRE
With AMC’s ‘Halt and Catch Fire’ co-creators Christopher Cantwell and Christopher Rogers, executive producer Melissa Bernstein, and Fortune’s Michal Lev-Ram.

—Article: Why We Can’t Stop Watching Movies and TV Shows About the Tech Industry, by Kia Kokalitcheva
—Video of the entire session

CHINA ROUNDTABLE: 21ST-CENTURY INNOVATION
With McKinsey’s Michael Chui, GGV Capital’s Jenny Lee, Flex’s Mike McNamara, CSC Venture Capital’s Veronica Wu, and CNN’s Jaime FlorCruz.

—Article: How China Is Preparing for a Decline In the Size of its Workforce, by Clifton Leaf

WHAT COMES AFTER UNICORNS?
With Accomplice’s Jeff Fagnan, Battery Ventures’ Roger Lee, Floodgate’s Ann Miura-Ko, Spark Capital Growth’s Megan Quinn, NEA’s Scott Sandell, and Fortune’s Dan Primack.

—Article: Why the Lack of Women in Venture Capital Continues to Persist, by Leena Rao

WHEN DIVERSITY IS IN THE DRIVER’S SEAT
With HP’s Lesley Slaton Brown, Code2040’s Laura Weidman Powers, Management Leadership for Tomorrow’s John Rice, Twitter’s Jeffrey Siminoff, NEA’s Melissa Taunton, and Fortune’s Michal Lev-Ram.

—Article: The Key to Tech Industry Diversity Is the White Male CEO, by Andrew Nusca

WIRING THE WORLD AROUND US, FROM ENERGY TO ELEVATORS
With ThyssenKrupp’s Patrick Bass, Aspect Ventures’ Jennifer Fonstad, Savant’s William Lynch, Zebra Technologies’ Jill Stelfox, Cree’s Chuck Swoboda, and Fortune’s Barb Darrow.

—Article: Why Connecting Devices to the Internet Is Just the First Step, by Jonathan Vanian

TUNING IN TO THE NEW WORLD OF TV
With Whalerock Industries’ Jeff Berman, Univision Communications’ Isaac Lee, Fox Networks Group’s Joe Marchese, Hulu’s Beatrice Springborn, and Fortune’s Erin Griffith.

—Article: ‘Cord-Cutters’ Are Not That Radical, by Kia Kokalitcheva

A CHIP FOR EVERY HOME (AND FACTORY AND HOSPITAL)
With Intel CEO Brian Krzanich and Fortune’s Adam Lashinsky.

—Article: Intel CEO Explains What Happened With That Donald Trump Fundraiser, by Barb Darrow
—Video: Here’s How Intel Plans to Re-Enter the Memory Market
—Video: This Is Intel’s Future in Tech

THIS TOY STORY STARTS WITH TECHNOLOGY
With Toys ‘R’ Us CEO David Brandon and Fortune’s Dan Primack.

—Article: Toys ‘R’ Us CEO Says He Wants Toy Chain to Return to New York City, by John Kell
—Video: Toys ‘R’ Us Has a Secret Weapon in the War Against Amazon
—Video of the entire session

10 TRENDS IN 10 MINUTES
With Culture Co-op CEO Melissa Lavigne-Delville.

—Video of the entire session

A LEAP INTO MIXED REALITY
With Magic Leap’s Rony Abovitz and Brian Wallace and Fortune’s Michal Lev-Ram.

—Article: Magic Leap Wants the Entire World to Be Your Computer Display, by Mathew Ingram
—Video of the entire session

PRESENTATION
With Girls Who Code CEO Reshma Saujani.

—Video of the entire session

THE INDUSTRIALIST’S DILEMMA
With GE’s Beth Comstock, Box’s Aaron Levie, and Fortune’s Alan Murray.

—Article: Why GE Is Willing to Make Mistakes, by Heather Clancy
—Video: The Strategy Behind GE’s Incentive System
—Video: Tesla Has a Larger Margin for Error because It’s a Disruptor
—Video: How GE IS Merging Digital and Industrial

ARTIFICIAL INTELLIGENCE: CAN A MACHINE MAKE YOU MILLIONS?
With Ellevest’s Sallie Krawcheck, Wealthfront’s Adam Nash, Felicis Ventures’ Aydin Senkut, Hearsay Social’s Clara Shih, and Fortune’s Adam Lashinsky.

—Article: These are the Jobs that Artificial Intelligence Will Eliminate First, by Dan Primack

DIGITAL TRANSFORMATION: RETHINKING SERVICE FOR THE SMART AGE
With Hyatt Hotels’ Mark Hoplamazian, OpenTable’s Christa Quarles, McDonalds’ Atif Rafiq, NBA’s David Stern, Slack’s April Underwood, and Fortune’s Clifton Leaf.

—No coverage available

WINNING THE NEW TALENT WARS
With TaskRabbit’s Stacy Brown-Philpot, Concur’s Elena Donio, Twilio’s Jeff Lawson, Fitbit’s James Park, DraftKings’ Jason Robins, and Fortune’s Aaron Task.

—Article: HBO’s ‘Silicon Valley’ Has Caused Some Soul-Searching At Tech Companies, by Erin Griffith

BUILDING AN AGILE ORGANIZATION FOR THE DIGITAL AGE
With General Assembly CEO Jake Schwartz and Fortune’s Michal Lev-Ram.

—Article: Why Employers Need to Empathize with ‘Entitled’ Millennials, by Jonathan Vanian

CAN THE TECH INDUSTRY STOP A NEW COLD WAR?
With the Stimson Center’s Brian Finlay, N Square’s Erika Gregory, ‘Command and Control’ author Eric Schlosser, and Fortune’s Adam Lashinsky.

—Can Tech Innovation Stop Nuclear Terrorism? by Clifton Leaf

BIG BUSINESS RACES TO THE STARS
With Accion Systems’ Natalya Brikner, NASA’s Philip McAlister, Virgin Galactic and The Spaceship Company’s George Whitesides, and Fortune’s Andrew Nusca.

—No coverage available

THE (BLOCK) CHAIN GANG: FUTURISTIC FINANCE
With Coinbase’s Brian Armstrong, Breyer Capital’s Jim Breyer, Chain’s Adam Ludwin, Netki’s Justin Newton, and Fortune’s Robert Hackett.

—No coverage available

BEING AIRBNB
With Airbnb’s Brian Chesky and Belinda Johnson and Fortune’s Andrew Nusca.

—Article: What Airbnb’s CEO Learned From a Bitter Fight With His Hometown, by Jeff John Roberts
—Article: Fixing Airbnb’s Discrimination Problem Is Harder Than It Seems, by Kia Kokalitcheva
—Video: Airbnb Is Still Trying to Resolve its Legal Issues in New York and San Fransisco
—Video: How AirBnB Is Trying to Make Itself More Inclusive
—Video: Airbnb Just Hit 100 Million Guest Arrivals

REPORT: CLOSING THE ED–TECH GAP
With the Aspen Institute’s Walter Isaacson, Orange County Public Schools’ Barbara Jenkins, and Time’s Susanna Schrobsdorff.

—Article: How to Revitalize Schools with Tech, by Robert Hackett

ALEXA, WHAT’S NEXT FOR AI?
With Amazon senior vice president David Limp and Fortune’s Adam Lashinsky.

—Article: Here Are Alexa’s Most Popular Skills, by Leena Rao
—Video: You Can Make Your Amazon Alexa Smarter

TO INFINITY AND BEYOND—WITH TRANSISTORS
With DST Global founder Yuri Milner and Fortune’s Adam Lashinsky.

—Article: This Internet Billionaire Wants to Solve the Mystery of the Universe, by Barb Darrow
—Video of the entire session

TAKING TALENT BEYOND THE COURT
With Springhill Entertainment’s Maverick Carter, Golden State Warriors’ Draymond Green, Warner Bros.’ Kevin Tsujihara, and Fortune’s Dan Primack.

—Article: Warriors’ Draymond Green Speaks About His Arrest For The First Time, by Katie Fehrenbacher
—Video: NBA Star Draymond Green Discusses His Arrest for Assault
—Video: Athletes Can Get Honest on Uninterrupted
—Video of the entire session

WHAT’S THE DEAL WITH DRONES?
With Airware’s Jonathan Downey, Descartes Labs’ Mark Johnson, Hogan Lovells’ Gretchen West, and Fortune’s Andrew Nusca.

—Article: Regulations Are Still a Top Concern Among Drone Experts, by Kia Kokalitcheva

MARKETING INNOVATION: THE CUSTOMER IS ALWAYS RIGHT
With Samsung’s Marc Mathieu, Facebook’s Sarah Personette, Clique Media Group’s Katherine Power, Dell’s Karen Quintos, Viant’s Tim Vanderhook, and Fortune’s Erin Griffith.

—No coverage available

CAN SMART GUNS BE SMARTER?
With the Smart Tech Challenges Foundation’s Margot Hirsch, the National Shooting Sports Foundation’s Lawrence Keane, Biofire Technologies’ Kai Kloepfer, and Fortune’s Dan Primack.

—Article: How Close Are We To Smart Guns? by Leena Rao

FINDING OPPORTUNITIES IN TURBULENT TIMES
With Breyer Capital’s Jim Breyer, Revolution’s Steve Case, GoDaddy’s Blake Irving, ‘The Creator’s Code’ author Amy Wilkinson, and Fortune’s Clifton Leaf.

—Article: Turbulent Times Might Actually Spark Rather Than Hinder Innovation, by Barb Darrow

A NEW MODEL FOR CONNECTIVITY
With Cisco CEO Chuck Robbins and Fortune’s Andrew Nusca.

—Article: Cisco CEO Chuck Robbins Has Had a Very Busy Year, by Jonathan Vanian
—Video: How Chuck Robbins Is Changing Cisco
—Video of the entire session

MAKING MOVIES FOR A GLOBAL AUDIENCE
With Legendary Entertainment’s Thomas Tull and Mary Parent and Fortune’s Michal Lev-Ram.

—Article: Movie Producer Thomas Tull Launches VC Fund, by Dan Primack
—Video: Why Legendary Entertainment Was Sold to a Chinese Conglomerate

BEYOND MOBILE
With PayPal CEO Dan Schulman and Fortune’s Andrew Nusca.

—Article: PayPal Is Okay If Millennials Don’t Know It Owns Venmo, by Leena Rao
—Video: This Is Venmo’s Secret Sauce
—Video of the entire session

MASTER COACH: WHAT I LEARNED FROM BILL CAMPBELL
With MetricStream’s Shellye Archambeau, Kleiner Perkins’ John Doerr, Uber’s Emil Michael, Intuit’s Brad Smith, and Fortune’s Adam Lashinsky.

—Article: Leadership Lessons from CEO Coach Bill Campbell, by Erin Griffith
—Video: Bill Campbell Focused on Diversity Before It Was Cool

Why Data Is The New Oil

by
Barb Darrow

@FortuneMagazine

July 11, 2016, 8:20 PM EDT

The field of artificial intelligence is red hot thanks in part to big companies like Google, Facebook, and Microsoft using AI-related techniques to train computers to recognize objects in photos and understand human language.

But these companies were only able to train their computers to perform these difficult feats because they have the enormous quantities of data that’s required. Companies that want to use artificial intelligence techniques like machine learning algorithms to improve their businesses will need to either have or acquire copious amounts of data, which will only become more valuable as the field of AI advances.

That’s one of the takeaways from a panel on artificial intelligence Monday in Aspen, Colo. during Fortune’s annual Brainstorm Tech conference.

“Data is the new oil,” Shivon Zilis, a partner with the venture capital firm Bloomberg Beta, said about data’s increasing value.

Get Data Sheet, Fortune’s technology newsletter.

Although companies like Google goog , Facebook fb , and Amazon amzn have open sourced their own artificial intelligence software so any programmer can access the code and use it to build their own apps, they are not making the necessary data available, Zilis explained. These companies are releasing these AI software toolkits for free so they can recruit more engineers to their companies, she said.

When it comes to competition, it’s the data these companies posses that’s more important than the actual AI software tools they use and release to the public.

David Kenny, the general manager of IBM’s ibm Watson data crunching service, agreed with Zilis and said “the value of data goes up every day AI advances.”

“Data will become a currency,” Kenny said. He also explained that only 20% of the world’s information is stored on the Internet, with the other 80% being privately held within companies and organizations.

Additionally, Zilis discussed the history of so-called “AI winters” in which the hype of AI failed to meet the general public’s expectations, and led to periods of years of declining research into AI during the mid-1970’s and the late 1980’s to early 1990’s.

Today, however, the rise of the cloud and the ability to access tremendous amounts of computing power to analyze huge amounts of data has the potential to strengthen the existing AI-related algorithms and lead to new more powerful algorithms. Because of these technological developments, Zilis does not believe companies will lose interest in AI.

For more about Brainstorm Tech, watch:

“Are we going to hit a winter?” asked Zilis. “Absolutely not.”

IBM Watson Brings AI Wonders to Cybersecurity

by
Barb Darrow

@FortuneMagazine

May 10, 2016, 6:57 AM EDT

After dominating its human competitors on the television gameshow Jeopardy!, IBM’s artificial intelligence platform Watson began dabbling with healthcare, pharmaceuticals, finance, education—even cooking. Now the machine is dipping its (robot) toes into the cybersecurity business.

Ginni Rometty, CEO of IBM ibm , will introduce a cybersecurity-specific version of Watson at an IBM computer security summit on Tuesday, the company said. The project, powered by IBM’s Bluemix cloud computing platform, includes a partnership between IBM and eight universities that begins in the fall. Some of the schools include the Massachusetts Institute of Technology, New York University, and Pennsylvania State University.

Get Data Sheet, Fortune’s technology newsletter.

IBM researchers have already begun feeding Watson with all sorts of computer security data sourced from its open access threat intelligence platform, called X-Force Exchange. The hope is that the trove of information on security vulnerabilities, spam messages, malware, and more will help the system become an expert assistant and advisor to security analysts.

Watson is also designed to ingest research papers, blog posts, news stories, media reports, alerts, textbooks, social media posts, and more to build up knowledge about all the latest cyber threats. Students at the partnering schools will help input and annotate this so-called unstructured data (meaning data that’s not easily machine readable) to train the system.

IBM believes there is a business opportunity in helping computer security pros make sense of the universe of literature and data surrounding cybersecurity. The company is banking on Watson being able to reduce the rate of false positives that turn up in corporate security operations centers, and being able to help address a shortage of talent in the industry.

For more on IBM Watson, watch:

“Even if the industry was able to fill the estimated 1.5 million open cyber security jobs by 2020, we’d still have a skills crisis in security,” said Marc van Zadelhoff, head of IBM Security, who landed the appointment earlier this year, in a statement. “By leveraging Watson’s ability to bring context to staggering amounts of unstructured data, impossible for people alone to process, we will bring new insights, recommendations, and knowledge to security professionals, bringing greater speed and precision to the most advanced cybersecurity analysts, and providing novice analysts with on-the-job training.”

(Zadelhoff had told Fortune at the beginning of the year that Watson integrations would be coming soon.)

Other schools involved in the initiative include California State Polytechnic University, Pomona; the University of New Brunswick; the University of Ottawa; the University of Waterloo; and the University of Maryland, Baltimore County. Additionally, the University of Maryland is slated to open an “accelerated cognitive cybersecurity laboratory” in partnership with IBM. It will explore machine learning and analytics applications for the new cyber-oriented Watson.

“It’s not about replacing humans, but about making them superhumans,” Caleb Barlow, vice president of strategic initiates at IBM Security, told Fortune. Following in the footsteps of its recently unveiled experimental blockchain program, the company seeks to debut a cybersecurity beta program with customers later this year, Barlow said.

IBM is betting on Watson’s AI-powered analytics being a key driver of its future growth. The company remains secretive about how the business is performing.

Pages:
1
2
3
4
5
«

Want the Full Story?