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ServiceNow acquires Loom Systems to expand AIOps coverage



ServiceNow announced today that it has acquired Loom Systems, an Israeli startup that specializes in AIOps. The companies did not reveal the purchase price.

IT operations collects tons of data across a number of monitoring and logging tools, way too much for any team of humans to keep up with. That’s why there are startups like Loom turning to AI to help sort through it. It can find issues and patterns in the data that would be challenging or impossible for humans to find. Applying AI to operations data in this manner has become known as AIOps in industry parlance.

ServiceNow is first and foremost a company trying to digitize the service process, however that manifests itself. IT service operations is a big part of that. Companies can monitor their systems, wait until a problem happens and then try to track down the cause and fix it — or, they can use the power of artificial intelligence to find potential dangers to the system health and neutralize them before they become major problems. That’s what an AIOps product like Loom’s can bring to the table.

Jeff Hausman, vice president and general manager of IT Operations Management at ServiceNow, sees Loom’s strengths merging with ServiceNow’s existing tooling to help keep IT systems running. “We will leverage Loom Systems’ log analytics capabilities to help customers analyze data, automate remediation and reduce L1 incidents,” he told TechCrunch.

Loom co-founder and CEO Gabby Menachem not surprisingly sees a similar value proposition. “By joining forces, we have the unique opportunity to bring together our AI innovations and ServiceNow’s AIOps capabilities to help customers prevent and fix IT issues before they become problems,” he said in a statement.

Loom has raised $16 million since it launched in 2015, according to PitchBook data. Its most recent round for $10 million was in November 2019. Today’s deal is expected to close by the end of this quarter.

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Heres our pick of the top six startups from Pause Fest



We’ve been dropping into the Australian startup scene increasingly over the years as the ecosystem has been building at an increasingly faster pace, most notably at our own TechCrunch Battlefield Australia in 2017. Further evidence that the scene is growing has come recently in the shape of the Pause Fest conference in Melbourne. This event has gone from strength to strength in recent years, and it is fast becoming a must-attend for Aussie startups aiming for both national international attention.

I was able to drop in virtually to interview a number of those showcased in the Startup Pitch Competition, so here’s a run-down of some of the stand-out companies.

Medinet Australia

Medinet Australia is a health-tech startup aiming to make healthcare more convenient and accessible to Australians by allowing doctors to do consultations with patients via an app. Somewhat similar to apps like Babylon Health, Medinet’s telehealth app allows patients to obtain clinical advice from a GP remotely; access prescriptions and have medications delivered; access pathology results; directly email their medical certificate to their employer; and access specialist referrals along with upfront information about specialists such as their fees, waitlist, and patient experience. They’ve raised $3M in Angel financing and are looking for institutional funding in due course. Given Australia’s vast distances, Medinet is well-placed to capitalize on the shift of the population towards much more convenient telehealth apps. (1st Place Winner)


Everty allows companies to easily manage, monitor and monetize Electric Vehicle charging stations. But this isn’t about infrastructure. Instead, they link up workplaces and accounting systems to the EV charging network, thus making it more like a “Salesforce for EV charging.” It’s available for both commercial and home charging tracking. It’s also raised an Angel round and is poised to raise further funding. (2nd Place Winner)

AI On Spectrum

It’s a sad fact that people with Autism statistically tend to die younger, and unfortunately, the suicide rate is much higher for Autistic people. “AI on Spectrum” takes an accessible approach in helping autistic kids and their families find supportive environments and feel empowered. The game encourages Autism sufferers to explore their emotional side and arms them with coping strategies when times get tough, applying AI and machine learning in the process to assist the user. (3rd Place Winner.)


Professional bee-keepers need a fast, reliable, easy-to-use record keeper for their bees and this startup does just that. But it’s also developing a software and sensor technology to give beekeepers more accurate analytics, allowing them to get an early-warning about issues and problems. Their technology could even, in the future, be used to alert for coming bushfires by sensing the changed behavior of the bees. (Hacker Exchange Additional Winner.)


Rechargeable batteries for things like cars can be re-used again, but the key to employing them is being able to extend their lives. Relectrify says its battery control software can unlock the full performance from every cell, increasing battery cycle life. It will also reduce storage costs by providing AC output without needing a battery inverter for both new and 2nd-life batteries. Its advanced battery management system combines power and electric monitoring to rapidly the check which are stronger cells and which are weaker making it possible to get as much as 30% more battery life, as well as deploying “2nd life storage”. So far, they have a project with Nissan and American Electric Power and have raised a Series A of $4.5 million. (SingularityU Additional Winner.)


Sadly, seniors and patients can contract bedsores if left too long. People can even die from bedsores. Furthermore, hospitals can end up in litigation over the issue. What’s needed is a technology that can prevent this, as well as predicting where on a patient’s body might be worst affected. That’s what Gabriel has come up with: using multi-modal technology to prevent and detect both falls and bedsores. Its passive monitoring technology is for the home or use in hospitals and consists of a resistive sheet with sensors connecting to a system which can understand the pressure on a bed. It has FDA approval, is patent-pending and is already working in some Hawaiian hospitals. It’s so far raised $2 million in Angel and is now raising money.

Here’s a taste of Pause Fest:

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Daily Crunch: Netflix makes autoplay previews optional



The Daily Crunch is TechCrunch’s roundup of our biggest and most important stories. If you’d like to get this delivered to your inbox every day at around 9am Pacific, you can subscribe here.

1. Netflix’s horrible autoplay previews can be turned off

Netflix’s autoplay trailers are now optional. That’s it. That’s the news.

And here’s how to turn them off now: Click “Manage Profiles,” choose your profile, then untick “Autoplay previews while browsing on all devices.”

2. Instagram prototypes letting IGTV creators monetize with ads

Instagram confirmed to TechCrunch that it has internally prototyped an Instagram Partner Program that would let creators earn money by showing advertisements along with their videos. By giving creators a sustainable and hands-off way to generate earnings from IGTV, those creators might be inspired to bring more and higher-quality content to the service.

3. Carta debuts fund to invest in startups that tap into its platform

Carta has created an investing vehicle called Carta Ventures. The well-funded unicorn hopes to foster an ecosystem around its core products and services.

4. SoftBank-backed Fair puts the brakes on weekly car rentals for Uber drivers

When Fair laid off 40% of its staff in October, CEO Scott Painter promised it wasn’t shuttering its leasing services to on-demand fleets. But just one week later, Painter was removed as CEO and replaced in the interim by Adam Hieber, a CFA from Fair investor SoftBank.

5. Is your startup using AI responsibly?

Since they started leveraging the technology, tech companies have received numerous accusations regarding the unethical use of artificial intelligence. Gramener’s Ganes Kesari says that to address the issue, fixing the model is not enough. (Extra Crunch membership required.)

6. NASA panel recommends Boeing software process reviews after revealing second Starliner issue

NASA’s Aerospace Safety Advisory Panel is recommending that Boeing’s software testing processes undergo a review, following the discovery of another problem with the on-board system that was in operation during the CST-100 Starliner uncrewed Space Station docking test launch in December.

7. Motorola embraces the stylus life on its budget G series

This morning, at an event in Chicago, Motorola introduced two new entries into the G line: the Moto G Power and Moto G Stylus, which will run $300 and $250, respectively.

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Defeated Chess Champ Garry Kasparov Has Made Peace With AI



Garry Kasparov is perhaps the greatest chess player in history. For almost two decades after becoming world champion in 1985, he dominated the game with a ferocious style of play and an equally ferocious swagger.

Outside the chess world, however, Kasparov is best known for losing to a machine. In 1997, at the height of his powers, Kasparov was crushed and cowed by an IBM supercomputer called Deep Blue. The loss sent shock waves across the world, and seemed to herald a new era of machine mastery over man.

The years since have put things into perspective. Personal computers have grown vastly more powerful, with smartphones now capable of running chess engines as powerful as Deep Blue alongside other apps. More significantly, thanks to recent progress in artificial intelligence, machines are learning and exploring the game for themselves.

Deep Blue followed hand-coded rules for playing chess. By contrast, AlphaZero, a program revealed by the Alphabet subsidiary DeepMind in 2017, taught itself to play the game at a grandmaster level simply by practicing over and over. Most remarkably, AlphaZero uncovered new approaches to the game that dazzled chess experts.

Last week, Kasparov returned to the scene of his famous Deep Blue defeat—the ballroom of a New York hotel—for a debate with AI experts organized by the Association for the Advancement of Artificial Intelligence. He met with WIRED senior writer Will Knight there to discuss chess, AI, and a strategy for staying a step ahead of machines. An edited transcript follows:

WIRED: What was it like to return to the venue where you lost to Deep Blue?

Garry Kasparov: I’ve made my peace with it. At the end of the day, the match was not a curse but a blessing, because I was a part of something very important. Twenty-two years ago, I would have thought differently. But things happen. We all make mistakes. We lose. What’s important is how we deal with our mistakes, with negative experience.

1997 was an unpleasant experience, but it helped me understand the future of human-machine collaboration. We thought we were unbeatable, at chess, Go, shogi. All these games, they have been gradually pushed to the side [by increasingly powerful AI programs]. But it doesn't mean that life is over. We have to find out how we can turn it to our advantage.

I always say I was the first knowledge worker whose job was threatened by a machine. But that helps me to communicate a message back to the public. Because, you know, nobody can suspect me of being pro-computers.

What message do you want to give people about the impact of AI?

I think it's important that people recognize the element of inevitability. When I hear outcry that AI is rushing in and destroying our lives, that it's so fast, I say no, no, it's too slow.

Every technology destroys jobs before creating jobs. When you look at the statistics, only 4 percent of jobs in the US require human creativity. That means 96 percent of jobs, I call them zombie jobs. They're dead, they just don’t know it.

For several decades we have been training people to act like computers, and now we are complaining that these jobs are in danger. Of course they are. We have to look for opportunities to create jobs that will emphasize our strengths. Technology is the main reason why so many of us are still alive to complain about technology. It's a coin with two sides. I think it's important that, instead of complaining, we look at how we can move forward faster.

When these jobs start disappearing, we need new industries, we need to build foundations that will help. Maybe it’s universal basic income, but we need to create a financial cushion for those who are left behind. Right now it's a very defensive reaction, whether it comes from the general public or from big CEOs who are looking at AI and saying it can improve the bottom line but it’s a black box. I think it's we still struggling to understand how AI will fit in.


A lot of people will have to contend with AI taking over some part of their jobs. What advice do you have for them?

There are different machines, and it is the role of a human and understand exactly what this machine will need to do its best. At the end of the day it's about combination. For instance, look at radiology. If you have a powerful AI system, I’d rather have an experienced nurse than a top-notch professor [use it]. A person with decent knowledge will understand that he or she must add only a little bit. But a big star in medicine will like to challenge the machines, and that destroys the communication.

People ask me, “What can you do to assist another chess engine against AlphaZero?” I can look at AlphaZero’s games and understand the potential weaknesses. And I believe it has made some inaccurate evaluations, which is natural. For example, it values bishop over knight. It sees over 60 million games that statistically, you know, the bishop was dominant in many more games. So I think it added too much advantage to bishop in terms of numbers. So what you should do, you should try to get your engine to a position where AlphaZero will make inevitable mistakes [based on this inaccuracy].

I often use this example. Imagine you have a very powerful gun, a rifle that can shoot a target 1 mile from where you are. Now a 1-millimeter change in the direction could end up with a 10-meter difference a mile away. Because the gun is so powerful, a tiny shift can actually make a big difference. And that's the future of human-machine collaboration.

With AlphaZero and future machines, I describe the human role as being shepherds. You just have to nudge the flock of intelligent algorithms. Just basically push them in one direction or another, and they will do the rest of the job. You put the right machine in the right space to do the right task.

How much progress do you think we’ve made toward human-level AI?

We don't know exactly what intelligence is. Even the best computer experts, the people on the cutting edge of computer science, they still have doubts about exactly what we're doing.

What we understand today is AI is still a tool. We are comfortable with machines making us faster and stronger, but smarter? It’s some sort of human fear. At the same time, what's the difference? We have always invented machines that help us to augment different qualities. And I think AI is just a great tool to achieve something that was impossible 10, 20 years ago.

How it will develop I don't know. But I don't believe in AGI [artificial general intelligence]. I don't believe that machines are capable of transferring knowledge from one open-ended system to another. So machines will be dominant in the closed systems, whether it's games, or any other world designed by humans.

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David Silver [the creator of AlphaZero] hasn’t answered my question about whether machines can set up their own goals. He talks about subgoals, but that’s not the same. That’s a certain gap in his definition of intelligence. We set up goals and look for ways to achieve them. A machine can only do the second part.

So far, we see very little evidence that machines can actually operate outside of these terms, which is clearly a sign of human intelligence. Let's say you accumulated knowledge in one game. Can it transfer this knowledge to another game, which might be similar but not the same? Humans can. With computers, in most cases you have to start from scratch.

Let’s talk about the ethics of AI. What do you think of the way the technology is being used for surveillance or weapons?

We know from history that progress cannot be stopped. So we have certain things we cannot prevent. If you [completely] restrict it in Europe, or America, it will just give an advantage to the Chinese. [But] I think we do need to exercise more public control over Facebook, Google, and other companies that generate so much data.


People say, oh, we need to make ethical AI. What nonsense. Humans still have the monopoly on evil. The problem is not AI. The problem is humans using new technologies to harm other humans.

AI is like a mirror, it amplifies both good and bad. We have to actually look and just understand how we can fix it, not say “Oh, we can create AI that will be better than us.” We are somehow stuck between two extremes. It's not a magic wand or Terminator. It's not a harbinger of utopia or dystopia. It's a tool. Yes, it's a unique tool because it can augment our minds, but it's a tool. And unfortunately we have enough political problems, both inside and outside the free world, that could be made much worse by the wrong use of AI.

Returning to chess, what do you make of AlphaZero’s style of play?

I looked at its games, and I wrote about them in an article that mentioned chess as the “drosophila of reasoning.” Every computer player is now too strong for humans. But we actually could learn more about our games. I can see how the millions of games played by AlphaGo during practice can generate certain knowledge that’s useful.

It was a mistake to think that if we develop very powerful chess machines, the game would be dull, that there will be many draws, maneuvers, or a game will be 1,800, 1,900 moves and nobody can break through. AlphaZero is totally the opposite. For me it was complementary, because it played more like Kasparov than Karpov! It found that it could actually sacrifice material for aggressive action. It’s not creative, it just sees the pattern, the odds. But this actually makes chess more aggressive, more attractive.

Magnus Carlsen [the current World Chess Champion] has said that he studied AlphaZero games, and he discovered certain elements of the game, certain connections. He could have thought about a move, but never dared to actually consider it; now we all know it works.

When you lost to DeepBlue, some people thought chess would no longer be interesting. Why do you think people are still interested in Carlsen?

You answered the question. We are still interested in people. Cars move faster than humans, but so what? The element of human competition is still there, because we want to know that our team, our guy, he or she is the best in the world.

The fact is that you have computers that dominate the game. It creates a sense of uneasiness, but on the other hand, it has expanded interest in chess. It’s not like 30 years ago, when Kasparov plays Karpov, and nobody dared criticize us even if we made a blunder. Now you can look at the screen and the machine tells you what's happening. So somehow machines brought many people into the game. They can follow, it's not a language they don't understand. AI is like an interface, an interpreter.

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