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After twenty years of Salesforce what Marc Benioff got right and wrong about the cloud

Grant Miller Contributor Share on Twitter Grant Miller is the co-founder of Replicated

As we enter the 20th year of Salesforce, there’s an interesting opportunity to reflect back on the change that Marc Benioff created with the software-as-a-service (SaaS) model for enterprise software with his launch of Salesforce.com.

This model has been validated by the annual revenue stream of SaaS companies, which is fast approaching $100 billion by most estimates, and it will likely continue to transform many slower-moving industries for years to come.

However, for the cornerstone market in IT — large enterprise-software deals — SaaS represents less than 25 percent of total revenue, according to most market estimates. This split is even evident in the most recent high profile “SaaS” acquisition of GitHub by Microsoft, with over 50 percent of GitHub’s revenue coming from the sale of their on-prem offering, GitHub Enterprise.  

Data privacy and security is also becoming a major issue, with Benioff himself even pushing for a U.S. privacy law on par with GDPR in the European Union. While consumer data is often the focus of such discussions, it’s worth remembering that SaaS providers store and process an incredible amount of personal data on behalf of their customers, and the content of that data goes well beyond email addresses for sales leads.

It’s time to reconsider the SaaS model in a modern context, integrating developments of the last nearly two decades so that enterprise software can reach its full potential. More specifically, we need to consider the impact of IaaS and “cloud-native computing” on enterprise software, and how they’re blurring the lines between SaaS and on-premises applications. As the world around enterprise software shifts and the tools for building it advance, do we really need such stark distinctions about what can run where?

Source: Getty Images/KTSDESIGN/SCIENCE PHOTO LIBRARY

The original cloud software thesis

In his book, Behind the Cloud, Benioff lays out four primary reasons for the introduction of the cloud-based SaaS model:

Realigning vendor success with customer success by creating a subscription-based pricing model that grows with each customer’s usag

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Original Content podcast ‘Queer Eye’ season two is even more of a tearjerker

It’s only been a couple months since we reviewed the first season of Netflix’s revival of Queer Eye, but the show’s Fab Five are already back with another eight episodes where they remake the homes, wardrobes and lives.

For season two, however, they mix things up a little — not only does the format feel more varied, but the folks being helped now include a woman and a transgendered man.

On the latest episode of the Original Content podcast, we’re joined by Henry Pickavet (editorial director at TechCrunch and co-host of the CTRL+T podcast) to discuss the show. We’re all fans: Queer Eye has its shortcomings, but it really works for us, with multiple episodes ending with tears, on- and off-screen.

We also recap some of the latest streaming and entertainment news, including AT&T’s acquisition of Time Warner, Comcast’s new bid for Fox and Netflix’s addition of Minecraft: Story Mode.

You can listen in the player below, subscribe using Apple Podcasts or find us in your podcast player of choice. If you like the show, please let us know by leaving a review on Apple. You also can send us feedback directly.

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The techlash

People hate hubris and hypocrisy more than they hate evil, which is, I think, why we’re seeing the beginnings of a bipartisan cultural backlash against the tech industry. A backlash which is wrongly conceived and wrongly targeted … but not entirely unfounded. It’s hard to shake the sense that, as an industry, we are currently abdicating some of our collective responsibility to the world.

Jeff Bezos and Elon Musk do a ton of objectively bad stuff, but I just want to be clear that the mere act of holding onto that much money in a world with this much inequality is in itself a brutally evil action, and alone makes them bad people.

— Joseph Fink (@PlanetofFinks) June 13, 2018

I don’t want to overstate the case. The tech industry remained the single most trusted entity in America as recently as last year, according to the Edelman Trust Barometer. Jeff Bezos is the wealthiest man in the world, and Elon Musk probably its highest-profile billionaire; of course they’re going to attract flak from all sides.

Furthermore, tech has become enormously more powerful and influential over the last decade. The Big Five tech companies now occupy the top five slots on the Fortune 500, whereas in 2008, Hewlett-Packard was tech’s lone Top Ten representative at #9. Power breeds resentment. Some kind of backlash was inevitable.

And yet — the tech industry is by some distance the least objectionable of the world’s power centers right now. The finance industry has become, to paraphrase Rolling Stone, a vampire squid wrapped around the our collective economic throat, siphoning off a quarter of our lifeblood via increasingly complex financial structures which provide very little benefit to the rest of us. But a combination of learned helplessness and lack of hypocrisy — in that very few hedge fund managers pretend to be making the world a better place for anyone but their clients — shields them from anything like the rancor they deserve.

Meanwhile, we’re in the midst of the worldwide right-wing populist uprising which has led governments around the world to treat desperate refugees like nonhuman scum; turning them away by the boatload in Europe; imprisoning them on a godforsaken remote island in Australia; tearing children from their parents and caging them in America.

Tesla and Amazon’s treatment of factory and warehouse work

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TechCrunch’s Startup Battlefield is coming soon to Beirut São Paolo and Lagos

Everyone knows there are thriving startup communities outside of obvious hubs, like San Francisco, Berlin, Bangalore and Beijing, but they don’t always get the support they deserve. Last year, TechCrunch took a major page from its playbook, the Startup Battlefield competition, and staged the event in Nairobi, Kenya to find the best early stage startup in Sub-Saharan Africa, and also to Sydney, Australia, to find the same for Australia and New Zealand. Both were successes, thanks to talented founders and the hard traveling TechCrunch team. And now we’re pleased to announce that we’re stepping up our commitment to emerging ecosystems.

TechCrunch is once again teaming up with Facebook, our partner for last year’s Nairobi event, to bring the Startup Battlefield to three major cities representing regions with vital, emerging startup communities. In Beirut, TechCrunch’s editors will strive to find the best early stage startup in the Middle East and North Africa. In São Paolo, the hunt is for the best in Latin America. And in Lagos, Nigeria, TechCrunch will once again find the top startup in Sub-Saharan Africa.

Early stage startups are welcome to apply. We will choose 15 companies in each region to compete, and we will provide travel support for the finalists to reach the host city. The finalists will also receive intensive coaching from TechCrunch’s editors to hone their pitches to a razor’s edge before they take the stage in front of top venture capitalists from the region and around the world. Winners will receive $25,000 plus a trip for two to the next TechCrunch Disrupt event, where they can exhibit free of charge, and, if qualified, have a chance to be selected to participate in the Startup Battlefield competition associated with that Disrupt. In the world of founders, the Startup Battlefield finalists are an elite; the more than 750 Startup Battlefield alums have raised over $8 billion and produced 100+ exits to date.

What are the dates? They will be finalized shortly but Beirut is on track for early October, São Paolo for early November, and Lagos in early December.  In the meantime, founders eager start an application for one of these Startup Battlefields may do so 
by visiting apply.techcrunch.com . Look for more details next week.

Interested in sponsoring one of the events? Email us at This email address is being protected from spambots. You need JavaScript enabled to view it.

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Facebook’s new AI research is a real eye-opener

There are plenty of ways to manipulate photos to make you look better, remove red eye or lens flare, and so on. But so far the blink has proven a tenacious opponent of good snapshots. That may change with research from Facebook that replaces closed eyes with open ones in a remarkably convincing manner.

It’s far from the only example of intelligent “in-painting,” as the technique is called when a program fills in a space with what it thinks belongs there. Adobe in particular has made good use of it with its “context-aware fill,” allowing users to seamlessly replace undesired features, for example a protruding branch or a cloud, with a pretty good guess at what would be there if it weren’t.

But some features are beyond the tools’ capacity to replace, one of which is eyes. Their detailed and highly variable nature make it particularly difficult for a system to change or create them realistically.

Facebook, which probably has more pictures of people blinking than any other entity in history, decided to take a crack at this problem.

It does so with a Generative Adversarial Network, essentially a machine learning system that tries to fool itself into thinking its creations are real. In a GAN, one part of the system learns to recognize, say, faces, and another part of the system repeatedly creates images that, based on feedback from the recognition part, gradually grow in realism.

From left to right: “Exemplar” images, source images, Photoshop’s eye-opening algorithm, and Facebook’s method.

In this case the network is trained to both recognize and replicate convincing open eyes. This could be done already, but as you can see in the examples at right, existing methods left something to be desired. They seem to paste in the eyes of the people without much consideration for consistency with the rest of the image.

Machines are naive that way: they have no intuitive understanding that opening one’s eyes does not also change the color of the skin around them. (For that matter, they have no intuitive understanding of eyes, color, or anything at all.)

What Facebook’s researchers did was to include “exemplar” data showing the target person with their eyes open, from which the GAN learns not just what eyes should go on t

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