Lucidworks raises $100M to expand in AI-powered search-as-a-service for organizations

Source: Tech News – Enterprise

If the sheer amount of information that we can tap into using the internet has made the world our oyster, then the huge success of Google is a testament to how lucrative search can be in helping to light the way through that data maze.

Now, in a sign of the times, a startup called Lucidworks, which has built an AI-based engine to help individual organizations provide personalised search services for their own users, has raised $100 million in funding. Lucidworks believes its approach can produce better and more relevant results than other search services in the market, and it plans to use the funding for its next stage of growth to become, in the words of CEO Will Hayes, “the world’s next important platform.”

The funding is coming from PE firm Francisco Partners? and ?TPG Sixth Street Partners?. Existing investors in the company include Top Tier Capital Partners, Shasta Ventures, Granite Ventures and Allegis Cyber.

Lucidworks has raised around $200 million in funding to date, and while it is not disclosing the valuation, the company says it been doubling revenues each year for the last three and counts companies like Reddit, Red Hat, REI, the US Census among some 400 others among its customers using its flagship product, Fusion. PitchBook notes that its last round in 2018 was at a modest $135 million, and my guess is that is up by quite some way.

The idea of building a business on search, of course, is not at all new, and Lucidworks works in a very crowded field. The likes of Amazon, Google and Microsoft have built entire empires on search — in Google’s and Microsoft’s case, by selling ads against those search results; in Amazon’s case, by generating sales of items in the search results — and they have subsequently productised that technology, selling it as a service to others.

Alongside that are companies that have been building search-as-a-service from the ground up — like Elastic, Sumo Logic and Splunk (whose founding team, coincidentally, went on to found Lucidworks…) — both for back-office processes as well as for services that are customer-facing.

In an interview, Hayes said that what sets Lucidworks apart is how it uses machine learning and other AI processes to personalise those results after “sorting through mountains of data”, to provide enterprise information to knowledge workers, shopping results on an e-commerce site to consumers, data to wealth managers, or whatever it is that is being sought.

Take the case of a shopping experience, he said by way of explanation. “If I’m on REI to buy hiking shoes, I don’t just want to see the highest-rated hiking shoes, or the most expensive,” he said.

The idea is that Lucidworks builds algorithms that bring in other data sources — your past shopping patterns, your location, what kind of walking you might be doing, what other people like you have purchased — to produce a more focused list of products that you are more likely to buy.

“Amazon has no taste,” he concluded, a little playfully.

Today, around half of Lucidworks’ business comes from digital commerce and digital content — searches of the kind described above for products, or monitoring customer search queries sites like RedHat or Reddit — and half comes from knowledge worker applications inside organizations.

The plan will be to continue that proportion, while also adding in other kinds of features — more natural language processing and more semantic search features — to expand the kinds of queries that can be made, and also cues that Fusion can use to produce results.

Interestingly, Hayes said that while it’s come up a number of times, Lucidworks doesn’t see itself ever going head-to-head with a company like Google or Amazon in providing a first-party search platform of its own. Indeed, that may be an area that has, for the time being at least, already been played out. Or it may be that we have turned to a time when walled gardens — or at least more targeted and curated experiences — are coming into their own.

“We still see a lot of runway in this market,” said Jonathan Murphy of Francisco Partners. “We were very attracted to the idea of next-generation search, on one hand serving internet users facing the pain of the broader internet, and on the other enterprises as an enterprise software product.” 

Lucidworks, it seems, has also entertained acquisition approaches, although Hayes declined to get specific about that. The longer-term goal, he said, “is to build something special that will stay here for a long time. The likelihood of needing that to be a public company is very high, but we will do what we think is best for the company and investors in the long run. But our focus and intention is to continue growing.”

Lucidworks raises 0M to expand in AI-powered search-as-a-service for organizations

Bias in AI: A problem recognized but still unresolved

Source: Microsoft more

There are those who praise the technology as the solution to some of humankind’s gravest problems, and those who demonize AI as the world’s greatest existential threat. Of course, these are two ends of the spectrum, and AI, surely, presents exciting opportunities for the future, as well as challenging problems to be overcome.

One of the issues that’s attracted much media attention in recent years has been the prospect of bias in AI. It’s a topic I wrote about in TechCrunch (Tyrant in the Code) more than two years ago. The debate is raging on.

At the time, Google had come under fire when research showed that when a user searched online for “hands,” the image results were almost all white; but when searching for “black hands,” the images were far more derogatory depictions, including a white hand reaching out to offer help to a black one, or black hands working in the earth. It was a shocking discovery that led to claims that, rather than heal divisions in society, AI technology would perpetuate them.

As I asserted two years ago, it’s little wonder that such instances might occur. In 2017, at least, the vast majority of people designing AI algorithms in the U.S. were white males. And while there’s no implication that those people are prejudiced against minorities, it would make sense that they pass on their natural, unconscious bias in the AI they create.

And it’s not just Google algorithms at risk from biased AI. As the technology becomes increasingly ubiquitous across every industry, it will become more and more important to eliminate any bias in the technology.

Understanding the problem

AI was indeed important and integral in many industries and applications two years ago, but its importance has, predictably, increased since then. AI systems are now used to help recruiters identify viable candidates, loan underwriters when deciding whether to lend money to customers and even judges when deliberating whether a convicted criminal will re-offend.

Of course, data can certainly help humans make more informed decisions using AI and data, but if that AI technology is biased, the result will be as well. If we continue to entrust the future of AI technology to a non-diverse group, then the most vulnerable members of society could be at a disadvantage in finding work, securing loans and being fairly tried by the justice system, plus much more.

AI is a revolution that will continue whether it’s wanted or not.

Fortunately, the issue around bias in AI has come to the fore in recent years, and more and more influential figures, organizations and political bodies are taking a serious look at how to deal with the problem.

The AI Now Institute is one such organization researching the social implications of AI technology. Launched in 2017 by research scientists Kate Crawford and Meredith Whittaker, AI Now focuses on the effect AI will have on human rights and labor, as well as how to safely integrate AI and how to avoid bias in the technology.

In May last year, the European Union put in place the General Data Protection Regulation (GDPR) — a set of rules that gives EU citizens more control over how their data is used online. And while it won’t do anything to directly challenge bias in AI technology, it will force European organizations (or any organization with European customers) to be more transparent in their use of algorithms. This will put extra pressure on companies to ensure they’re confident in the origins of the AI they’re using.

And while the U.S. doesn’t yet have a similar set of regulations around data use and AI, in December 2017, New York’s city council and mayor passed a bill calling for more transparency in AI, prompted by reports the technology was causing racial bias in criminal sentencing.

Despite research groups and government bodies taking an interest in the potentially damaging role biased AI could play in society, the responsibility largely falls to the businesses creating the technology, and whether they’re prepared to tackle the problem at its core. Fortunately, some of the largest tech companies, including those that have been accused of overlooking the problem of AI bias in the past, are taking steps to tackle the problem.

Microsoft, for instance, is now hiring artists, philosophers and creative writers to train AI bots in the dos and don’ts of nuanced language, such as to not use inappropriate slang or inadvertently make racist or sexist remarks. IBM is attempting to mitigate bias in its AI machines by applying independent bias ratings to determine the fairness of its AI systems. And in June last year, Google CEO Sundar Pichai published a set of AI principles that aims to ensure the company’s work or research doesn’t create or reinforce bias in its algorithms.

Demographics working in AI

Tackling bias in AI does indeed require individuals, organizations and government bodies to take a serious look at the roots of the problem. But those roots are often the people creating the AI services in the first place. As I posited in “Tyrant in the Code” two years ago, any left-handed person who’s struggled with right-handed scissors, ledgers and can-openers will know that inventions often favor their creators. The same goes for AI systems.

New data from the Bureau of Labor Statistics shows that the professionals who write AI programs are still largely white males. And a study conducted last August by Wired and Element AI found that only 12% of leading machine learning researchers are women.

This isn’t a problem completely overlooked by the technology companies creating AI systems. Intel, for instance, is taking active steps in improving gender diversity in the company’s technical roles. Recent data indicates that women make up 24% of the technical roles at Intel — far higher than the industry average. And Google is funding AI4ALL, an AI summer camp aimed at the next generation of AI leaders, to expand its outreach to young women and minorities underrepresented in the technology sector.

However, the statistics show there is still a long way to go if AI is going to reach the levels of diversity required to stamp out bias in the technology. Despite the efforts of some companies and individuals, technology companies are still overwhelmingly white and male.

Solving the problem of bias in AI

Of course, improving diversity within the major AI companies would go a long way toward solving the problem of bias in the technology. Business leaders responsible for distributing the AI systems that impact society will need to offer public transparency so that bias can be monitored, incorporate ethical standards into the technology and have a better understanding of who the algorithm is supposed to be targeting.

Governments and business leaders alike have some serious questions to ponder.

But without regulations from government bodies, these types of solutions could come about too slowly, if at all. And while the European Union has put in place GDPR that in many ways tempers bias in AI, there are no strong signs that the U.S. will follow suit any time soon.

Government, with the help of private researchers and think tanks, is moving quickly in the direction and trying to grapple with how to regulate algorithms. Moreover, some companies like Facebook are also claiming regulation could be beneficial. Nevertheless, high regulatory requirements for user-generated content platforms could help companies like Facebook by making it nearly impossible to compete for new startups entering the market.

The question is, what is the ideal level of government intervention that won’t hinder innovation?

Entrepreneurs often claim that regulation is the enemy of innovation, and with such a potentially game-changing, relatively nascent technology, any roadblocks should be avoided at all cost. However, AI is a revolution that will continue whether it’s wanted or not. It will go on to change the lives of billions of people, and so it clearly needs to be heading in an ethical, unbiased direction.

Governments and business leaders alike have some serious questions to ponder, and not much time to do it. AI is a technology that’s developing fast, and it won’t wait for indecisiveness. If the innovation is allowed to go on unchecked, with few ethical guidelines and a non-diverse group of creators, the results may lead to a deepening of divisions in the U.S. and worldwide.

Bias in AI: A problem recognized but still unresolved

Microsoft PowerPoint gets an AI presentation coach

Source: Microsoft more

Love it or hate it, Microsoft’s PowerPoint is a ubiquitous tool in the corporate world. Over the course of the last few years, Microsoft started to bring some of its AI smarts to PowerPoint to help you design good-looking slides. Today, it’s launching a number of updates and new features that make this even easier. Even the best-designed presentation isn’t going to have much of an impact if you’re not a good public speaker. That’s a skill that takes a lot of practice to master and to help you get better, Microsoft today also announced Presenter Coach for PowerPoint, a new AI tool that gives you feedback while you’re practicing your presentation in front of your computer.

Microsoft’s AI can’t tell you if your jokes will land, of course, but the new coaching feature gives you real-time feedback on your pacing, for example, tell you whether you are using inclusive language and how many filler words you use. It also makes sure that you don’t commit the greatest sin of presenting: just reading the slides.

After your rehearsal session, PowerPoint will show you a dashboard with a summary of your performance and what to focus on to improve your skills.

This feature will first come to PowerPoint on the web and then later to the Office 365 desktop version.

As for the visual design, Microsoft today added new features like Designer theme ideas, which automatically recommends photos, styles and colors are you write your presentation. This feature is now rolling out for Office 365 subscribers on Windows, Mac and on the web.

If you work in a large corporation, then chances are you have to use your brand’s house style. With Designer for branded templates, companies can now define their brand guidelines and logos so that Design Ideas takes these into account as PowerPoint suggests new designes. This feature is now rolling out to to Office 365 Insiders subscribers on Windows 10 and Mac.

No announcement is complete without some vanity metrics, of course, so today, Microsoft announced that PowerPoint users have now used Designer to create and keep 1 billion slides since it launched in 2016 (and surely, they created quite a few more but discarded them for various reasons). Hopefully, that means the world has seen fewer bad presentations in the last few years and with today’s launch of the new coaching features, maybe that means we have to hear fewer bad presentations soon, too.

Microsoft PowerPoint gets an AI presentation coach

RealityEngines.AI raises $5.25M seed round to make ML easier for enterprises

Source: Tech News – Enterprise

RealityEngines.AI, a research startup that wants to help enterprises make better use of AI, even when they only have incomplete data, today announced that it has raised a $5.25 million seed funding round. The round was led by former Google CEO and Chairman Eric Schmidt and Google founding board member Ram Shriram. Khosla Ventures, Paul Buchheit, Deepchand Nishar, Elad Gil, Keval Desai, Don Burnette and others also participated in this round.

The fact that the service was able to raise from this rather prominent group of investors clearly shows that its overall thesis resonates. The company, which doesn’t have a product yet, tells me that it specifically wants to help enterprises make better use of the smaller and noisier datasets they have and provide them with state-of-the-art machine learning and AI systems that they can quickly take into production. It also aims to provide its customers with systems that can explain their predictions and are free of various forms of bias, something that’s hard to do when the system is essentially a black box.

As RealityEngines CEO Bindu Reddy, who was previously the head of products for Google Apps, told me the company plans to use the funding to build out its research and development team. The company, after all, is tackling some of the most fundamental and hardest problems in machine learning right now — and that costs money. Some, like working with smaller datasets, already have some available solutions like generative adversarial networks that can augment existing datasets and that RealityEngines expects to innovate on.

Reddy is also betting on reinforcement learning as one of the core machine learning techniques for the platform.

Once it has its product in place, the plan is to make it available as a pay-as-you-go managed service that will make machine learning more accessible to large enterprise, but also to small and medium businesses, which also increasingly need access to these tools to remain competitive.

RealityEngines.AI raises .25M seed round to make ML easier for enterprises

Oh no, there’s A.I. whiskey now

Source: Microsoft more

Forget all those whiskey brands from musicians and celebs — there’s A.I. whiskey now. Microsoft this week announced it has teamed up with Finnish tech company Fourkind and Sweden-based distillery Mackmyra Whisky to create the “world’s first whisky developed with artificial intelligence.”

Oh no!

Here’s how it will work.

As part of the distillation process, whiskey first spends time — typically years — sitting in charred wooden casks. This turns the clear liquor a darker color, and gives it a unique flavor. How long it stays in the casks, and what the casks held before — like bourbon, wine, sherry, etc. — helps create a specific recipe. Master distillers tweak all these variables along with the different ingredients used to create the whiskey in the first place to come up with a variety of blends.

Until now, this entire process is done by humans with a specialized set of skills. For the A.I. blend, Mackmyra is turning part of the job over to the machines.

The distillery is feeding its existing recipes, sales data and customer preferences to machine learning models, so the A.I. can suggest what recipes it should make next.

The A.I., Mackmyra says, is capable of generating over 70 million different recipes. And it will highlight those it predicts will be most popular and of the highest quality, based on the cask types that are currently on hand.

These models are powered by Microsoft’s Azure cloud platform and Azure cognitive services. Fourkind developed the A.I. algorithms involved, explains Microsoft in its announcement.

However, the distillery notes it’s not actually replacing its Master Blenders with A.I. Instead, it’s using the A.I. to create the recipes which are then curated by the (still human) experts.

“The work of a Master Blender is not at risk,” insists Angela D’Orazio, Mackmyra’s Master Blender. “While the whiskey recipe is created by A.I., we still benefit from a person’s expertise and knowledge, especially the human sensory part, that can never be replaced by any program. We believe that the whiskey is A.I.-generated, but human-curated. Ultimately, the decision is made by a person.”

Microsoft says this is the first time A.I. has been used to augment the process of making whiskey. The finished product will be available in Autumn 2019.

Despite not knowing how the juice turns out, Fourkind wants to turn its algorithms to other industries where complex recipes are involved — including those for other beverages, and also things like perfumes, sweets, or sneaker designs.

This would not be the first time that A.I. has been put to work in a more artistic field.

For example, at Google’s I/O developer conference this month, the company showed off how A.I. could be used in artistic endeavors — including music, visual art, and even fashion.

Of course, when A.I. is tasked with making art, the end results tend to be strange, unworldly and sometimes a little frightening.

Which begs the question: how the hell will an A.I. whiskey taste?

(via TNW


Oh no, there’s A.I. whiskey now

LogMeIn acquires chatbot and AI startup Nanorep for up to $50M

Source: Tech News – Enterprise
 LogMeIn, the company that provides authentication and other connectivity solutions for those who connect remotely to networks and services, has made another acquisition to expand the products it offers to customers, specifically in its new Bold360 CRM platform, launched in June. The company has picked up Nanorep, a startup out of Israel that develops chatbots and other AI-based tools to… Read MoreLogMeIn acquires chatbot and AI startup Nanorep for up to M