Incorta raises $30M Series C for ETL-free data processing solution

Source: Tech News – Enterprise

Incorta, a startup founded by former Oracle executives who want to change the way we process large amounts data, announced a $30 million Series C today led by Sorenson Capital.

Other investors participating in the round included GV (formerly Google Ventures), Kleiner Perkins, M12 (formerly Microsoft Ventures), Telstra Ventures and Ron Wohl. Today’s investment brings the total raised to $75 million, according to the company.

Incorta CEO and co-founder Osama Elkady says he and his co-founders were compelled to start Inccorta because they saw so many companies spending big bucks for data projects that were doomed to fail. “The reason that drove me and three other guys to leave Oracle and start Incorta is because we found out with all the investment that companies were making around data warehousing and implementing advanced projects, very few of these projects succeeded,” Elkady told TechCrunch.

A typical data project of involves ETL (extract, transform, load). It’s a process that takes data out of one database, changes the data to make it compatible with the target database and adds it to the target database.

It takes time to do all of that, and Incorta is trying to give access to the data much faster by stripping out this step. Elkady says that this allows customers to make use of the data much more quickly, claiming they are reducing the process from one that took hours to one that takes just seconds. That kind of performance enhancement is garnering attention.

Rob Rueckert, managing director for lead investor Sorenson Capital sees a company that’s innovating in a mature space. “Incorta is poised to upend the data warehousing market with innovative technology that will end 30 years of archaic and slow data warehouse infrastructure,” he said in a statement.

The company says revenue is growing by leaps and bounds, reporting 284% year over year growth (although they did not share specific numbers). Customers include Starbucks, Shutterfly and Broadcom.

The startup, which launched in 2013, currently has 250 employees with developers in Egypt and main operations in San Mateo, California. They recently also added offices in Chicago, Dubai and Bangalore.


Incorta raises M Series C for ETL-free data processing solution

Rimeto lands $10M Series A to modernize the corporate directory

Source: Tech News – Enterprise

The notion of the corporate directory has been around for many years, but in a time of more frequent turnover and shifting responsibilities, the founders of Rimeto, a 3 year old San Francisco startup, wanted to update it to reflect those changes.

Today, the company announced a $10 million Series A investment from USVP, Bow Capital, Floodgate and Ray Dalio, founder of Bridgewater Associates.

Co-founder Ted Zagat says that the founders observed shifting workplace demographics and changes in the way people work. They believed it required a better to way to locate people inside large organizations, which typically used homegrown methods or relied on Outlook or other corporate email systems.

“On one hand, we have people being asked to work much more collaboratively and cross-functionally. On the other, is an increasingly fragmented workplace. Employees really need help to be able to understand each other and work together effectively. That’s a real challenge for them,” Zagat explained.

Rimeto has developed a richer directory by sitting between various corporate systems like HR, CRM and other tools that contain additional details about the employee. It of course includes a name, title, email and phone like the basic corporate system, but it goes beyond that to find areas of expertise, projects the person is working on and other details that can help you find the right person when you’re searching the directory.

Rimeto product version 1 1

Rimeto directory on mobile and web. Screenshot: Rimeto

Zagat says that by connecting to these various corporate systems and layering on a quality search tool with a variety of filters to narrow the search, it can help employees connect to others inside an organization more easily, something that is often difficult to do in large companies.

The tool can be accessed via web or mobile app, or incorporated into a company intranet. It could also be accessed from a tool like Slack or Microsoft Teams.

The three founders — Zagat, Neville Bowers and Maxwell Hayman — all previously worked at Facebook. Unlike a lot of early stage startups, the company has paying customers (although it won’t share exactly how many) and reports that it’s cash-flow positive. Up to this point, the three founders had boot-strapped the company, but they wanted to go out and raise some capital to begin to expand more rapidly.


Rimeto lands M Series A to modernize the corporate directory

Salesforce is acquiring ClickSoftware for $1.35B

Source: Tech News – Enterprise

Another day, another Salesforce acquisition. Just days after closing the hefty $15.7 billion Tableau deal, the company opened its wallet again, this time announcing it has bought field service software company ClickSoftware for a tidy $1.35 billion.

This one is could help beef up the company’s field service offering, which falls under the Service Cloud umbrella. In its June earnings report, the company reported that Service Cloud crossed the $1 billion revenue threshold for the first time. This acquisition is designed to keep those numbers growing.

“Our acquisition of ClickSoftware will not only accelerate the growth of Service Cloud, but drive further innovation with Field Service Lightning to better meet the needs of our customers,” Bill Patterson, EVP and GM of Salesforce Service Cloud said in a statement announcing the deal.

ClickSoftware is actually older than Salesforce having been founded in 1997. The company went public in 2000, and remained listed until it went private again in 2015 in a deal with private equity company Francisco Partners, which bought it for $438 million. Francisco did alright for itself, holding onto the company for four years before more than doubling its money.

The deal is expected to close in the Fall and is subject to the normal regulatory approval process.


Salesforce is acquiring ClickSoftware for .35B

With MapR fire sale, Hadoop’s promise has fallen on hard times

Source: Tech News – Enterprise

If you go back about a decade, Hadoop was hot and getting hotter. It was a platform for processing big data, just as big data was emerging from the domain of a few web-scale companies to one where every company was suddenly concerned about processing huge amounts of data. The future was bright, an open source project with a bunch of startups emerging to fulfill that big data promise in the enterprise.

Three companies in particular emerged out of that early scrum — Cloudera, Hortonworks and MapR — and between them raised more than $1.5 billion. The lion’s share of that went to Cloudera in one massive chunk when Intel Capital invested a whopping $740 million in the company. But times have changed.

2018 china ipos

Via TechCrunch, Crunchbase, Infogram

Falling hard

Just yesterday, HPE bought the assets of MapR, a company that had raised $280 million. The deal was pegged at under $50 million, according to multiple reports. That’s not what you call a healthy return on investment.

Rookout lands $8M Series A to expand debugging platform

Source: Tech News – Enterprise

Rookout, a startup that provides debugging across a variety of environments including serverless and containers, announced an $8 million Series A investment today. It plans to use the money to expand beyond its debugging roots.

The round was led by Cisco Investments along with existing investors TLV Partners and Emerge. Nat Friedman, CEO of GitHub; John Kodumal, CTO and co-founder of LaunchDarkly, and Raymond Colletti, VP of revenue at Codecov also participated.

Rookout from day one has been working to provide production debugging and collection capabilities to all platforms,” Or Weis, co-founder and CEO of Rookout told TechCrunch. That has included serverless like AWS Lambda, containers and Kubernetes and Platform as a Service like Google App Engine and Elastic Beanstalk

The company is also giving visibility into platforms that are sometimes hard to observe because of the ephemeral nature of the technology, and that go beyond its pure debugging capabilities. “In the last year, we’ve discovered that our customers are finding completely new ways to use Rookout’s code-level data collection capabilities and that we need to accommodate, support and enhance the many varied uses of code-level observability and pipelining,” Weiss said in a statement.

It was particularly telling that a company like Cisco was deeply involved in the round. Rob Salvagno, vice president of Cisco Global Corporate Development and Cisco Investments, likes the developer focus of the company.

“Developers have become key influencers of enterprise IT spend. By collecting data on-demand without re-deploying, Rookout created a Developer-centric software, which short-circuits complexities in the production debugging, increases Developer efficiency and reduces the friction which exists between IT Ops and Developers,” Salvagno said in a statement.

Rookout, which launched in 2017, has offices in San Francisco and Tel Aviv with a total of 20 employees so far. It has raised over $12 million.


Rookout lands M Series A to expand debugging platform

Cockroach Labs announces $55M Series C to battle industry giants

Source: Tech News – Enterprise

Cockroach Labs, makers of CockroachDB, sits in a tough position in the database market. On one side, it has traditional database vendors like Oracle, and on the other there’s AWS and its family of databases. It takes some good technology and serious dollars to compete with those companies. Cockroach took care of the latter with a $55 million Series C round today.

The round was led by Altimeter Capital and Tiger Global along with existing investor GV. Other existing investors including Benchmark, Index Ventures, Redpoint Ventures, FirstMark Capital and Work-Bench also participated. Today’s investment brings the total raised to over $110 million, according to the company.

Spencer Kimball, co-founder and CEO, says the company is building a modern database to compete with these industry giants. “CockroachDB is architected from the ground up as a cloud native database. Fundamentally, what that means is that it’s distributed, not just across nodes in a single data center, which is really table stakes as the database gets bigger, but also across data centers to be resilient. It’s also distributed potentially across the planet in order to give a global customer base what feels like a local experience to keep the data near them,” Kimball explained.

At the same time, even while it has a cloud product hosted on AWS, it also competes with several AWS database products including Amazon Aurora, Redshift and DynamoDB. Much like MongoDB, which changed its open source licensing structure last year, Cockroach did as well, for many of the same reasons. They both believed bigger players were taking advantage of the open source nature of their products to undermine their markets.

“If you’re trying to build a business around an open source product, you have to be careful that a much bigger player doesn’t come along and extract too much of the value out of the open source product that you’ve been building and maintaining,” Kimball explained.

As the company deals with all of these competitive pressures, it takes a fair bit of money to continue building a piece of technology to beat the competition, while going up against much deeper-pocketed rivals. So far the company has been doing well with Q1 revenue this year doubling all of last year. Kimball indicated that Q2 could double Q1, but he wants to keep that going, and that takes money.

“We need to accelerate that sales momentum and that’s usually what the Series C is about. Fundamentally, we have, I think, the most advanced capabilities in the market right now. Certainly we do if you look at the differentiator around just global capability. We nevertheless are competing with Oracle on one side, and Amazon on the other side. So a lot of this money is going towards product development too,” he said.

Cockroach Labs was founded in 2015, and is based in New York City.


Cockroach Labs announces M Series C to battle industry giants

Dasha AI is calling so you don’t have to

Source: Tech News – Enterprise

While you’d be hard pressed to find any startup not brimming with confidence over the disruptive idea they’re chasing, it’s not often you come across a young company as calmly convinced it’s engineering the future as Dasha AI.

The team is building a platform for designing human-like voice interactions to automate business processes. Put simply, it’s using AI to make machine voices a whole lot less robotic.

“What we definitely know is this will definitely happen,” says CEO and co-founder Vladislav Chernyshov. “Sooner or later the conversational AI/voice AI will replace people everywhere where the technology will allow. And it’s better for us to be the first mover than the last in this field.”

“In 2018 in the US alone there were 30 million people doing some kind of repetitive tasks over the phone. We can automate these jobs now or we are going to be able to automate it in two years,” he goes on. “If you multiple it with Europe and the massive call centers in India, Pakistan and the Philippines you will probably have something like close to 120M people worldwide… and they are all subject for disruption, potentially.”

The New York based startup has been operating in relative stealth up to now. But it’s breaking cover to talk to TechCrunch — announcing a $2M seed round, led by RTP Ventures and RTP Global: An early stage investor that’s backed the likes of Datadog and RingCentral. RTP’s venture arm, also based in NY, writes on its website that it prefers engineer-founded companies — that “solve big problems with technology”. “We like technology, not gimmicks,” the fund warns with added emphasis.

Dasha’s core tech right now includes what Chernyshov describes as “a human-level, voice-first conversation modelling engine”; a hybrid text-to-speech engine which he says enables it to model speech disfluencies (aka, the ums and ahs, pitch changes etc that characterize human chatter); plus “a fast and accurate” real-time voice activity detection algorithm which detects speech in under 100 milliseconds, meaning the AI can turn-take and handle interruptions in the conversation flow. The platform can also detect a caller’s gender — a feature that can be useful for healthcare use-cases, for example.

Another component Chernyshov flags is “an end-to-end pipeline for semi-supervised learning” — so it can retrain the models in real time “and fix mistakes as they go” — until Dasha hits the claimed “human-level” conversational capability for each business process niche. (To be clear, the AI cannot adapt its speech to an interlocutor in real-time — as human speakers naturally shift their accents closer to bridge any dialect gap — but Chernyshov suggests it’s on the roadmap.)

“For instance, we can start with 70% correct conversations and then gradually improve the model up to say 95% of correct conversations,” he says of the learning element, though he admits there are a lot of variables that can impact error rates — not least the call environment itself. Even cutting edge AI is going to struggle with a bad line.

The platform also has an open API so customers can plug the conversation AI into their existing systems — be it telephony, Salesforce software or a developer environment, such as Microsoft Visual Studio.

Currently they’re focused on English, though Chernyshov says the architecture is “basically language agnostic” — but does requires “a big amount of data”.

The next step will be to open up the dev platform to enterprise customers, beyond the initial 20 beta testers, which include companies in the banking, healthcare and insurance sectors — with a release slated for later this year or Q1 2020.

Test use-cases so far include banks using the conversation engine for brand loyalty management to run customer satisfaction surveys that can turnaround negative feedback by fast-tracking a response to a bad rating — by providing (human) customer support agents with an automated categorization of the complaint so they can follow up more quickly. “This usually leads to a wow effect,” says Chernyshov.

Ultimately, he believes there will be two or three major AI platforms globally providing businesses with an automated, customizable conversational layer — sweeping away the patchwork of chatbots currently filling in the gap. And of course Dasha intends their ‘Digital Assistant Super Human Alike’ to be one of those few.

“There is clearly no platform [yet],” he says. “Five years from now this will sound very weird that all companies now are trying to build something. Because in five years it will be obvious — why do you need all this stuff? Just take Dasha and build what you want.”

“This reminds me of the situation in the 1980s when it was obvious that the personal computers are here to stay because they give you an unfair competitive advantage,” he continues. “All large enterprise customers all over the world… were building their own operating systems, they were writing software from scratch, constantly reinventing the wheel just in order to be able to create this spreadsheet for their accountants.

“And then Microsoft with MS-DOS came in… and everything else is history.”

That’s not all they’re building, either. Dasha’s seed financing will be put towards launching a consumer-facing product atop its b2b platform to automate the screening of recorded message robocalls. So, basically, they’re building a robot assistant that can talk to — and put off — other machines on humans’ behalf.

Which does kind of suggest the AI-fuelled future will entail an awful lot of robots talking to each other… 🤖🤖🤖

Chernyshov says this b2c call screening app will most likely be free. But then if your core tech looks set to massively accelerate a non-human caller phenomenon that many consumers already see as a terrible plague on their time and mind then providing free relief — in the form of a counter AI — seems the very least you should do.

Not that Dasha can be accused of causing the robocaller plague, of course. Recorded messages hooked up to call systems have been spamming people with unsolicited calls for far longer than the startup has existed.

Dasha’s PR notes Americans were hit with 26.3BN robocalls in 2018 alone — up “a whopping” 46% on 2017.

Its conversation engine, meanwhile, has only made some 3M calls to date, clocking its first call with a human in January 2017. But the goal from here on in is to scale fast. “We plan to aggressively grow the company and the technology so we can continue to provide the best voice conversational AI to a market which we estimate to exceed $30BN worldwide,” runs a line from its PR.

After the developer platform launch, Chernyshov says the next step will be to open up access to business process owners by letting them automate existing call workflows without needing to be able to code (they’ll just need an analytic grasp of the process, he says).

Later — pegged for 2022 on the current roadmap — will be the launch of “the platform with zero learning curve”, as he puts it. “You will teach Dasha new models just like typing in a natural language and teaching it like you can teach any new team member on your team,” he explains. “Adding a new case will actually look like a word editor — when you’re just describing how you want this AI to work.”

His prediction is that a majority — circa 60% — of all major cases that business face — “like dispatching, like probably upsales, cross sales, some kind of support etc, all those cases” — will be able to be automated “just like typing in a natural language”.

So if Dasha’s AI-fuelled vision of voice-based business process automation come to fruition then humans getting orders of magnitude more calls from machines looks inevitable — as machine learning supercharges artificial speech by making it sound slicker, act smarter and seem, well, almost human.

But perhaps a savvier generation of voice AIs will also help manage the ‘robocaller’ plague by offering advanced call screening? And as non-human voice tech marches on from dumb recorded messages to chatbot-style AIs running on scripted rails to — as Dasha pitches it — fully responsive, emoting, even emotion-sensitive conversation engines that can slip right under the human radar maybe the robocaller problem will eat itself? I mean, if you didn’t even realize you were talking to a robot how are you going to get annoyed about it?

Dasha claims 96.3% of the people who talk to its AI “think it’s human”, though it’s not clear what sample size the claim is based on. (To my ear there are definite ‘tells’ in the current demos on its website. But in a cold-call scenario it’s not hard to imagine the AI passing, if someone’s not paying much attention.)

The alternative scenario, in a future infested with unsolicited machine calls, is that all smartphone OSes add kill switches, such as the one in iOS 13 — which lets people silence calls from unknown numbers.

And/or more humans simply never pick up phone calls unless they know who’s on the end of the line.

So it’s really doubly savvy of Dasha to create an AI capable of managing robot calls — meaning it’s building its own fallback — a piece of software willing to chat to its AI in future, even if actual humans refuse.

Dasha’s robocall screener app, which is slated for release in early 2020, will also be spammer-agnostic — in that it’ll be able to handle and divert human salespeople too, as well as robots. After all, a spammer is a spammer.

“Probably it is the time for somebody to step in and ‘don’t be evil’,” says Chernyshov, echoing Google’s old motto, albeit perhaps not entirely reassuringly given the phrase’s lapsed history — as we talk about the team’s approach to ecosystem development and how machine-to-machine chat might overtake human voice calls.

“At some point in the future we will be talking to various robots much more than we probably talk to each other — because you will have some kind of human-like robots at your house,” he predicts. “Your doctor, gardener, warehouse worker, they all will be robots at some point.”

The logic at work here is that if resistance to an AI-powered Cambrian Explosion of machine speech is futile, it’s better to be at the cutting edge, building the most human-like robots — and making the robots at least sound like they care.

Dasha’s conversational quirks certainly can’t be called a gimmick. Even if the team’s close attention to mimicking the vocal flourishes of human speech — the disfluencies, the ums and ahs, the pitch and tonal changes for emphasis and emotion — might seem so at first airing.

In one of the demos on its website you can hear a clip of a very chipper-sounding male voice, who identifies himself as “John from Acme Dental”, taking an appointment call from a female (human), and smoothly dealing with multiple interruptions and time/date changes as she changes her mind. Before, finally, dealing with a flat cancelation.

A human receptionist might well have got mad that the caller essentially just wasted their time. Not John, though. Oh no. He ends the call as cheerily as he began, signing off with an emphatic: “Thank you! And have a really nice day. Bye!”

If the ultimate goal is Turing Test levels of realism in artificial speech — i.e. a conversation engine so human-like it can pass as human to a human ear — you do have to be able to reproduce, with precision timing, the verbal baggage that’s wrapped around everything humans say to each other.

This tonal layer does essential emotional labor in the business of communication, shading and highlighting words in a way that can adapt or even entirely transform their meaning. It’s an integral part of how we communicate. And thus a common stumbling block for robots.

So if the mission is to power a revolution in artificial speech that humans won’t hate and reject then engineering full spectrum nuance is just as important a piece of work as having an amazing speech recognition engine. A chatbot that can’t do all that is really the gimmick.

Chernyshov claims Dasha’s conversation engine is “at least several times better and more complex than [Google] Dialogflow, [Amazon] Lex, [Microsoft] Luis or [IBM] Watson”, dropping a laundry list of rival speech engines into the conversation.

He argues none are on a par with what Dasha is being designed to do.

The difference is the “voice-first modelling engine”. “All those [rival engines] were built from scratch with a focus on chatbots — on text,” he says, couching modelling voice conversation “on a human level” as much more complex than the more limited chatbot-approach — and hence what makes Dasha special and superior.

“Imagination is the limit. What we are trying to build is an ultimate voice conversation AI platform so you can model any kind of voice interaction between two or more human beings.”

Google did demo its own stuttering voice AI — Duplex — last year, when it also took flak for a public demo in which it appeared not to have told restaurant staff up front they were going to be talking to a robot.

Chernyshov isn’t worried about Duplex, though, saying it’s a product, not a platform.

“Google recently tried to headhunt one of our developers,” he adds, pausing for effect. “But they failed.”

He says Dasha’s engineering staff make up more than half (28) its total headcount (48), and include two doctorates of science; three PhDs; five PhD students; and ten masters of science in computer science.

It has an R&D office in Russian which Chernyshov says helps makes the funding go further.

“More than 16 people, including myself, are ACM ICPC finalists or semi finalists,” he adds — likening the competition to “an Olympic game but for programmers”. A recent hire — chief research scientist, Dr Alexander Dyakonov — is both a doctor of science professor and former Kaggle No.1 GrandMaster in machine learning. So with in-house AI talent like that you can see why Google, uh, came calling…

Dasha

 

But why not have Dasha ID itself as a robot by default? On that Chernyshov says the platform is flexible — which means disclosure can be added. But in markets where it isn’t a legal requirement the door is being left open for ‘John’ to slip cheerily by. Bladerunner here we come.

The team’s driving conviction is that emphasis on modelling human-like speech will, down the line, allow their AI to deliver universally fluid and natural machine-human speech interactions which in turn open up all sorts of expansive and powerful possibilities for embeddable next-gen voice interfaces. Ones that are much more interesting than the current crop of gadget talkies.

This is where you could raid sci-fi/pop culture for inspiration. Such as Kitt, the dryly witty talking car from the 1980s TV series Knight Rider. Or, to throw in a British TV reference, Holly the self-depreciating yet sardonic human-faced computer in Red Dwarf. (Or indeed Kryten the guilt-ridden android butler.) Chernyshov’s suggestion is to imagine Dasha embedded in a Boston Dynamics robot. But surely no one wants to hear those crawling nightmares scream…

Dasha’s five-year+ roadmap includes the eyebrow-raising ambition to evolve the technology to achieve “a general conversational AI”. “This is a science fiction at this point. It’s a general conversational AI, and only at this point you will be able to pass the whole Turing Test,” he says of that aim.

“Because we have a human level speech recognition, we have human level speech synthesis, we have generative non-rule based behavior, and this is all the parts of this general conversational AI. And I think that we can we can — and scientific society — we can achieve this together in like 2024 or something like that.

“Then the next step, in 2025, this is like autonomous AI — embeddable in any device or a robot. And hopefully by 2025 these devices will be available on the market.”

Of course the team is still dreaming distance away from that AI wonderland/dystopia (depending on your perspective) — even if it’s date-stamped on the roadmap.

But if a conversational engine ends up in command of the full range of human speech — quirks, quibbles and all — then designing a voice AI may come to be thought of as akin to designing a TV character or cartoon personality. So very far from what we currently associate with the word ‘robotic’. (And wouldn’t it be funny if the term ‘robotic’ came to mean ‘hyper entertaining’ or even ‘especially empathetic’ thanks to advances in AI.)

Let’s not get carried away though.

In the meanwhile, there are ‘uncanny valley’ pitfalls of speech disconnect to navigate if the tone being (artificially) struck hits a false note. (And, on that front, if you didn’t know ‘John from Acme Dental’ was a robot you’d be forgiven for misreading his chipper sign off to a total time waster as pure sarcasm. But an AI can’t appreciate irony. Not yet anyway.)

Nor can robots appreciate the difference between ethical and unethical verbal communication they’re being instructed to carry out. Sales calls can easily cross the line into spam. And what about even more dystopic uses for a conversation engine that’s so slick it can convince the vast majority of people it’s human — like fraud, identity theft, even election interference… the potential misuses could be terrible and scale endlessly.

Although if you straight out ask Dasha whether it’s a robot Chernyshov says it has been programmed to confess to being artificial. So it won’t tell you a barefaced lie.

Dasha

How will the team prevent problematic uses of such a powerful technology?

“We have an ethics framework and when we will be releasing the platform we will implement a real-time monitoring system that will monitor potential abuse or scams, and also it will ensure people are not being called too often,” he says. “This is very important. That we understand that this kind of technology can be potentially probably dangerous.”

“At the first stage we are not going to release it to all the public. We are going to release it in a closed alpha or beta. And we will be curating the companies that are going in to explore all the possible problems and prevent them from being massive problems,” he adds. “Our machine learning team are developing those algorithms for detecting abuse, spam and other use cases that we would like to prevent.”

There’s also the issue of verbal ‘deepfakes’ to consider. Especially as Chernyshov suggests the platform will, in time, support cloning a voiceprint for use in the conversation — opening the door to making fake calls in someone else’s voice. Which sounds like a dream come true for scammers of all stripes. Or a way to really supercharge your top performing salesperson.

Safe to say, the counter technologies — and thoughtful regulation — are going to be very important.

There’s little doubt that AI will be regulated. In Europe policymakers have tasked themselves with coming up with a framework for ethical AI. And in the coming years policymakers in many countries will be trying to figure out how to put guardrails on a technology class that, in the consumer sphere, has already demonstrated its wrecking-ball potential — with the automated acceleration of spam, misinformation and political disinformation on social media platforms.

“We have to understand that at some point this kind of technologies will be definitely regulated by the state all over the world. And we as a platform we must comply with all of these requirements,” agrees Chernyshov, suggesting machine learning will also be able to identify whether a speaker is human or not — and that an official caller status could be baked into a telephony protocol so people aren’t left in the dark on the ‘bot or not’ question. 

“It should be human-friendly. Don’t be evil, right?”

Asked whether he considers what will happen to the people working in call centers whose jobs will be disrupted by AI, Chernyshov is quick with the stock answer — that new technologies create jobs too, saying that’s been true right throughout human history. Though he concedes there may be a lag — while the old world catches up to the new.

Time and tide wait for no human, even when the change sounds increasingly like we do.


Dasha AI is calling so you don’t have to

Why AWS gains big storage efficiencies with E8 acquisition

Source: Tech News – Enterprise

AWS is already the clear market leader in the cloud infrastructure market, but it’s never been an organization that rests on its past successes. Whether it’s a flurry of new product announcements and enhancements every year, or making strategic acquisitions.

When it bought Israeli storage startup E8 yesterday, it might have felt like a minor move on its face, but AWS was looking, as it always does, to find an edge and reduce the costs of operations in its data centers. It was also very likely looking forward to the next phase of cloud computing. Reports have pegged the deal at between $50 and $60 million.

What E8 gives AWS for relatively cheap money is highly advanced storage capabilities, says Steve McDowell, senior storage analyst at Moor Research and Strategy. “E8 built a system that delivers extremely high-performance/low-latency flash (and Optane) in a shared-storage environment,” McDowell told TechCrunch.

The Exit: The acquisition charting Salesforce’s future

Source: Microsoft more

Before Tableau was the $15.7 billion key to Salesforce’s problems, it was a couple of founders arguing with a couple of venture capitalists over lunch about why its Series A valuation should be higher than $12 million pre-money.

Salesforce has generally been one to signify corporate strategy shifts through their acquisitions, so you can understand why the entire tech industry took notice when the cloud CRM giant announced its priciest acquisition ever last month.

The deal to acquire the Seattle-based data visualization powerhouse Tableau was substantial enough that Salesforce CEO Marc Benioff publicly announced it was turning Seattle into its second HQ. Tableau’s acquisition doesn’t just mean big things for Salesforce. With the deal taking place just days after Google announced it was paying $2.6 billion for Looker, the acquisition showcases just how intense the cloud wars are getting for the enterprise tech companies out to win it all.

The Exit is a new series at TechCrunch. It’s an exit interview of sorts with a VC who was in the right place at the right time but made the right call on an investment that paid off. [Have feedback? Shoot me an email at lucas@techcrunch.com]

Scott Sandell, a general partner at NEA (New Enterprise Associates) who has now been at the firm for 25 years, was one of those investors arguing with two of Tableau’s co-founders, Chris Stolte and Christian Chabot. Desperate to close the 2004 deal over their lunch meeting, he went on to agree to the Tableau founders’ demands of a higher $20 million valuation, though Sandell tells me it still feels like he got a pretty good deal.

NEA went on to invest further in subsequent rounds and went on to hold over 38% of the company at the time of its IPO in 2013 according to public financial docs.

I had a long chat with Sandell, who also invested in Salesforce, about the importance of the Tableau deal, his rise from associate to general partner at NEA, who he sees as the biggest challenger to Salesforce, and why he thinks scooter companies are “the worst business in the known universe.”

The interview has been edited for length and clarity. 


Lucas Matney: You’ve been at this investing thing for quite a while, but taking a trip down memory lane, how did you get into VC in the first place? 

Scott Sandell: The way I got into venture capital is a little bit of a circuitous route. I had an opportunity to get into venture capital coming out of Stanford Business School in 1992, but it wasn’t quite the right fit. And so I had an interest, but I didn’t have the right opportunity.

The Exit: The acquisition charting Salesforce’s future

Source: Tech News – Enterprise

Before Tableau was the $15.7 billion key to Salesforce’s problems, it was a couple of founders arguing with a couple of venture capitalists over lunch about why its Series A valuation should be higher than $12 million pre-money.

Salesforce has generally been one to signify corporate strategy shifts through their acquisitions, so you can understand why the entire tech industry took notice when the cloud CRM giant announced its priciest acquisition ever last month.

The deal to acquire the Seattle-based data visualization powerhouse Tableau was substantial enough that Salesforce CEO Marc Benioff publicly announced it was turning Seattle into its second HQ. Tableau’s acquisition doesn’t just mean big things for Salesforce. With the deal taking place just days after Google announced it was paying $2.6 billion for Looker, the acquisition showcases just how intense the cloud wars are getting for the enterprise tech companies out to win it all.

The Exit is a new series at TechCrunch. It’s an exit interview of sorts with a VC who was in the right place at the right time but made the right call on an investment that paid off. [Have feedback? Shoot me an email at lucas@techcrunch.com]

Scott Sandell, a general partner at NEA (New Enterprise Associates) who has now been at the firm for 25 years, was one of those investors arguing with two of Tableau’s co-founders, Chris Stolte and Christian Chabot. Desperate to close the 2004 deal over their lunch meeting, he went on to agree to the Tableau founders’ demands of a higher $20 million valuation, though Sandell tells me it still feels like he got a pretty good deal.

NEA went on to invest further in subsequent rounds and went on to hold over 38% of the company at the time of its IPO in 2013 according to public financial docs.

I had a long chat with Sandell, who also invested in Salesforce, about the importance of the Tableau deal, his rise from associate to general partner at NEA, who he sees as the biggest challenger to Salesforce, and why he thinks scooter companies are “the worst business in the known universe.”

The interview has been edited for length and clarity. 


Lucas Matney: You’ve been at this investing thing for quite a while, but taking a trip down memory lane, how did you get into VC in the first place? 

Scott Sandell: The way I got into venture capital is a little bit of a circuitous route. I had an opportunity to get into venture capital coming out of Stanford Business School in 1992, but it wasn’t quite the right fit. And so I had an interest, but I didn’t have the right opportunity.