1010Computers | Computer Repair & IT Support

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Freebird flies off with $8M to rescue passengers after flight cancellations

Published October 30, 2018

There are few things more irritating than a canceled flight, whether it’s on your way to a friend’s wedding, a conference or to celebrate a holiday back home. Wouldn’t it be nifty if technology could put an end to our travel woes? Freebird, a travel rebooking service, has raised an $8 million Series A to do just that.

The startup charges a minimum of $19 per flight — more depending on distance, time of year, location and more — to independent travelers and companies that partner with the service to help travelers rebook flights after cancellations or other “disruption events.” Most of the time, flights are on-time and without issue, which means that most of the time, Freebird pockets all of its customer’s cash. But if there is a disruption event, Freebird guarantees it will rebook you with just three taps of your phone and without any additional charge.

American Express Ventures has led the round, with support from Citi Ventures, PAR Capital Ventures, General Catalyst and Accomplice. Freebird is currently in discussions with Amex and Citi, as well as other banks, to roll its travel benefits into their corporate card services. To date, the startup works with 100 corporate clients and 10 corporate travel agency partners, including BCD Travel. Freebird says it expects to support 250,000 travelers this year.

Founded in 2015 by Ethan Bernstein, Cambridge, Mass.-based Freebird aggregates data on flight patterns to predict the probability of a flight disruption. If the probability is high, Freebird charges more for access to its mobile rebooking tool.

“If you’re flying out of Buffalo in the winter, it’s going to be a higher-risk flight,” Freebird chief executive officer Bernstein told TechCrunch. “If you’re flying out of Phoenix in the summer, you’re at a very low risk of being disrupted. We understand those risks and we are able to price our product differently based on those factors.”

Freebird has raised a total of $16.5 million in funding to date. It’s one of many travel technology startups to bring in venture capital this year. IfOnly, a marketplace for experiences, secured $20 million in April; luggage startup Away brought in a $50 million in June; and travel activities platform Klook raised $200 million in August, to name a few.

Freebird, though focused specifically on flights, says its experiences are at the forefront of its business model.

“There are a million different products that will help you automate your life but one of the things we are focused on is transforming personal experiences,” Bernstein said. “Do they go through these disruption events tearing their hair out or do they go through it knowing that they have control, agency, support and information? It’s funny what happens when people deal with uncertainty; uncertainty is the worst. As soon you give people information, human support and technology to help them solve their problems, they experience the event so much differently.”

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Sentieo raises $19M to be the AI-powered Bloomberg Terminal

Published October 30, 2018

To get an edge on the market, investors must look beyond traditional financial info like revenue and profits. Our every online activity generates data exhaust, like web traffic, Twitter mentions, app downloads and search trends. It’s the ability to overlay the old and new data sets to spot surprising trends that will set the best traders apart. Sentieo wants to be their tool.

Sentieo is an investment research software suite that uses AI to scan financial documents, analyze alternative data sets and create visualizations. The fintech SAAS startup now has 700 customers, including top hedge funds plus mutual funds, Fortune 500s and investment banks that pay around $500 to $1,000 per month per license. That’s a lot cheaper than a $21,000 yearly Bloomberg Terminal subscription. [Correction: Sentieo charges $500 to $1000 per month, not per year.]

Now Sentieo is ready to crank up its name recognition with a sales and marketing blitz fueled by a new $19 million Series A round led by Centana, a $250 million growth equity firm focused on fintech SAAS. Now with $30 million in total funding, the 160-person startup plans to “Educate [traders] that ‘hey, this product is built by people who sat in your seats,’” says CEO Alap Shah.

Sentieo charts Search Trends data and Sentieo Index data on Facebook versus the social network’s revenue.

Ten years ago, Shah was making the Wall Street rounds after graduating from Harvard in economics. He was an analyst in consulting at Novantas, private equity at Castanea, and worked for hedge funds Viking Global and Citadel. “It became clear that there were some really big holes in my process where software wasn’t meeting my needs. Importantly, there was a hole around search,” Shah tells me. “We’ve grown accustomed to going to Google. But unfortunately that’s just not the way the old-school financial data programs are structured.”

Sentieo co-founder and CEO Alap Shah

So he built his own. “I used all the financial tools out there: Capital IQ, FactSet, Bloomberg — each had their strengths and weaknesses. But they were all over 20 years old, so they pre-date the cloud, pre-date SAAS, pre-date mobile!” With Sentieo, he wanted to develop a tool that could understand the nuances of business momentum before it showed up in the balance sheets.

Sentieo does have a traditional financial equity data terminal with real-time pricing. But there’s also a machine learning and natural language processing-powered document search tool that can sort through SEC documents, earnings call transcripts, press releases and more. It taps Alexa web traffic data, Apptopia app download rates and Twitter chatter, as well as Thomson Reuters analyst estimates and fundamentals. Customers can annotate files, organize ideas, generate visualizations and share their insights through Sentieo’s Notebook.

For example, Sentieo could look through all of Tesla’s earnings calls and financial documents for mentions of guidance on Model 3 production volume. It could highlight them all, analyze the sentiment of those mentions and chart them against Tesla’s share price. Or you could search for all the companies starting to list President Trump as a risk factor for their business, which would surface how the medical cannabis companies are concerned about Attorney General Jeff Sessions’ stance on legalization.

Sentieo’s synonym library allows it to hunt down different ways of saying the same thing with the goal of not forcing investors — or their dutiful analysts — to read through 100-page 10-Q documents manually. “You can get the same information at 10x the speed with something like Sentieo,” Shah claims. It wants to a be a “research management system,” like a Salesforce CRM for tracking investment ideas.

But Sentieo’s 65-person India-based engineering must keep data from all 50 feeds, 25 million documents and 64,000 equities flowing to keep customers satisfied. There are a ton of moving parts, and Sentieo is competing with much bigger companies. Beyond Bloomberg, there are lots of alternative data providers out there. And Microsoft’s software suite also has plenty of info management tools.

Sentieo’s hope is to emerge as an aggregator of information sources and an annotation tool that benefits from being purposefully designed for what analysts need. If Robinhood is on one side of the spectrum making investing easy for novice traders, Sentieo is on the other end making investing smarter for experts. “It’s really at the bleeding edge of how you get the data today,” Shah concludes. “For every company driven by consumer demand, there are all these little breadcrumbs being left all over the internet.”

[Disclosure: I briefly rented a room in an apartment where Shah lived five years ago and I know him from the San Francisco social scene frequented by many Silicon Valley figures.]

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How to watch the live stream for Apple’s iPad and Mac keynote

Published October 30, 2018

Apple is holding a keynote today at the Brooklyn Academy of Music’s Howard Gilman Opera House, and the company is expected to unveil a brand new iPad Pro as well as updated Mac computers. The event starts at 10 AM in New York (7 AM in San Francisco, 2 PM in London, 3 PM in Paris), you’ll be able to watch the event as the company is streaming it live.

If you live in Europe and already put a note in your calendar, make sure you got the time right as daylight saving time has yet to happen in the U.S. New York is currently 4 hours behind London, 5 hours behind Paris, etc.

Apple is likely to unveil a new iPad Pro to replace the 10.5-inch and 12.9-inch iPad Pro. Rumor has it that it’ll look nothing like your current iPad. The device should get rounded corners, thinner bezels and a Face ID sensor. Apple could also switch to USB-C instead of Lightning and refresh the Apple Pencil.

On the Mac front, the MacBook Air could get a refresh. This could be Apple’s new entry-level laptop. But it should sport a retina display for the first time. There could also be a new Mac Mini of some sort after all those years without an update.

Finally, maybe Apple will tell us why the AirPower charging mat is still not available. Apple might also update the AirPods. But maybe it’ll happen later.

If you have a recent Apple TV, you can download the Apple Events app in the App Store. It lets you stream today’s event and rewatch old events. Users with pre-App Store Apple TVs can simply turn on their devices. Apple is pushing out the “Apple Events” channel so that you can watch the event.

And if you don’t have an Apple TV, the company also lets you live-stream the event from the Apple Events section on its website. This video feed now works in all major browsers — Safari, Google Chrome, Mozilla Firefox and Microsoft Edge.

So to recap, here’s how you can watch today’s Apple event:

  • On iOS: Safari.
  • On the Mac: Safari, Google Chrome or Mozilla Firefox.
  • On Windows: Google Chrome, Mozilla Firefox or Microsoft Edge.
  • An Apple TV with the Apple Events app in the App Store.

Of course, you also can read TechCrunch’s live blog if you’re stuck at work and really need our entertaining commentary track to help you get through your day. We have a big team in the room this year.

Apple Fall Event 2018

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Concord raises $25 million for its contract management platform

Published October 30, 2018

Concord is raising a new $25 million funding round led by Tenaya Capital, with existing investors CRV and Alven also participating. The company is building a platform that makes it easier to manage your contracts all the way from writing them to signing them.

Even if you used a service like DocuSign to sign a contract in the past, chances are you or the sender used Microsoft Word to write the contract. It’s fine if you’re the only one working on this contract. But it can quickly become a mess as your legal team gets larger.

“It’s ultimately bringing a B2C experience to a really complex B2B experience,” VP of Marketing Travis Bickham told me.

And one of the company’s main challenge has been to make it convenient for all teams in your organization. If you work in human resources, you’re dealing with HR contracts. If you’re an office manager, you may need to sign a contract to order a new fridge. If you’re on the sales team, you want to make sure your client signs a contract. The procurement team also wants some sort of legal proof from its partners. And the list goes on.

Concord lets you create templates and workflows. For instance, the most basic contracts don’t require the same attention to details. A non-disclosure agreement is pretty standard. You just have to replace some fields and make the person sign it.

You can create an approval process for more complicated contracts. For instance, you can say that the legal team has to approve any sales contract above $100,000.

Concord has also built integrations with third-party tools. For instance, you can generate a contract in Salesforce using Concord’s integration.

There are currently 80 people working for Concord in San Francisco and Paris. With today’s funding round, the company plans to hire more people, get more clients, target bigger companies, etc. Concord currently works with 200,000 companies.

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Valued at $500M, investors say HeadSpin is ‘one of the fastest-scaling software companies’ ever

Published October 30, 2018

HeadSpin has closed a $20 million Series B, valuing the provider of mobile application performance software at $500 million. New investors ICONIQ Capital, Battery Ventures and EQT Ventures participated in the funding round. Existing backers GV, Telstra Ventures, Danhua Capital, Nexus Ventures Partners and NextWorld Capital did not participate.

The company emerged from stealth last year with Manish Lachwani at the helm. Lachwani was the former principal architect of the Amazon Kindle, chief technology officer of mobile gaming company Zynga and co-founder and chief technology officer of Google-acquired Appurify, which helped developers automate testing and optimization of their mobile apps and websites.

He’s been in the application performance management business for a long time; under his leadership, Palo Alto-based HeadSpin has quickly grown into one of the fastest growing, though relatively unknown, startups in Silicon Valley.

“What HeadSpin has been able to achieve in its first three years is remarkable, and it has already attracted dozens of major clients across the mobile ecosystem,” ICONIQ partner Will Griffith said in a statement. “The company is quickly becoming the new standard of record for all mobile ecosystem players going forward. It’s one of the fastest-scaling software companies we’ve seen.”

HeadSpin works with Tinder, DocuSign and some 200 other app providers, allowing the companies to test and monitor their apps in real-time and on real devices before, during and after an app is released. The AI-enabled platform gives developers the ability to experience their app just as any regular user would and highlights high priority issues so companies can quickly resolve customer’s problems at scale.

Founded in 2015, HeadSpin says it expects to double revenue in 2018 but did not disclose any financial metrics.

Chief technology officer Brien Colwell is the other half of the company’s founding team. Colwell is the founder and former CEO of Nextop.io, a Y Combinator graduate and app optimization startup. Colwell and Lachwani are joined by HeadSpin’s head of product Sriram Krishnan, Tinder’s former head of international growth. Krishnan joined HeadSpin in October 2017 after working with HeadSpin’s toolset in his role at the app-based dating company.

“When I signed up for HeadSpin, I found out how phenomenal the product was,” Krishnan told TechCrunch .

“A lot of what we built was predicated on the fact that the mobile ecosystem is still very new,” he added. “If you think about the apps world, it’s only been around 10 years … It’s the Wild West out there when it comes to understanding performance.”

 

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Ian Small, former head of TokBox, takes over as Evernote CEO from Chris O’Neill

Published October 30, 2018

Former TokBox head Ian Small is replacing Chris O’Neill as CEO of Evernote, the note-taking and productivity app company said this morning. In a blog post, Small said that the leadership change was announced to employees this morning by Evernote’s board. “We are all hugely appreciative of the energy and dedication Chris has shown over the last three years, and in particular for putting Evernote on solid financial footing so we can continue to build for the future,” he wrote.

Small added, “When Stepan Pachikov founded Evernote, he had a vision for how technology could augment memory and how an app could change the way we relate to information at home and at work. Evernote has been more successful at making progress towards Stepan’s dreams than he could have imagined, but Stepan and I both think that there is more to explore and more to invent.”

O”Neill had been Evernote’s CEO since 2015, when he took over the position from co-founder Phil Libin. Small previously served as CEO of TokBox, which operates the OpenTok video calling platform, from 2009 to 2014, and then as its chairman from 2014 to July of this year.

O’Neill’s departure as CEO is the latest significant leadership shift for Evernote, which has withstood several key executive departures over the last few months. In early September, we reported that the company had lost several senior executives, including CTO Anirban Kundu, CFO Vincent Toolan, CPO Erik Wrobel, and head of HR Michelle Wagner, as it sought funding in a potential down-round from the unicorn valuation it hit in 2012. According to TechCrunch’s sources, Evernote had struggled to grow its base of paid users and active users, as well as enterprise clients, for the last six years.

Then a few weeks later, Evernote announced that had to lay off 54 people, or about 15 percent of its workforce. O’Neill wrote a blog post about the company’s future growth strategy, including streamlining specific functions like sales so it could focus on product development and engineering.

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Lime hires its first chief business officer amid push into car-sharing

Published October 30, 2018

After four months “on the beach,” per his LinkedIn profile, Uber’s former global head of business and corporate development has a new gig. Lime has hired David Richter (pictured) as its first-ever chief business officer and interim chief financial officer.

Based in San Francisco, Richter will be overseeing the bike- and e-scooter-sharing startup’s business operations. Richter spent more than four years at Uber leading the ride-hailing giant’s global business development, corporate development, experiential marketing, autonomous vehicle alliances and brand relevance teams. He left in May after expressing frustrations with a series of departures in his group, according to The Information.

“As Lime continues to grow, David will bring in unparalleled expertise, particularly in the realm of business development and corporate partnerships, as well as in managing our overall business strategy and deal flow,” Lime co-founder and chief executive officer Toby Sun said in a statement. “His leadership experience, coupled with his keen understanding of the fast-moving shared mobility industry will be a huge advantage to our company as we continue to expand our global footprint.”

Lime is said to be completing the fundraising circuit right now, asking investors for a valuation north of $3 billion. The company, which entered the unicorn club in June, has raised a total of $467 million to date from GV, Andreessen Horowitz, IVP, Section 32, GGV Capital and more.

The company is using the buckets of capital to expand beyond bikes and scooters. Last Monday, rumors emerged that it was planning a brick-and-mortar push. The company confirmed that it would indeed build scooter “lifestyle stores” in major U.S. and international markets, starting with Santa Monica, Calif.

The next day on stage at the JD Power Automotive Roundtable, Lime announced its official foray into car-sharing. The company has since applied for a car-sharing permit in Seattle and plans to rent out small electric vehicles, which it’s calling “transit pods,” by the end of the year.

According to Axios, Lime plans to spend $50 million on the pods, which will cost $1 for consumers to start, plus an additional 40 cents per minute.

“You can expect electric vehicles to be an additional micro-mobility option for Lime riders to choose from within the Lime app soon,” a spokesperson for Lime said in a statement provided to TechCrunch. “More details on timing, specs of the vehicle, locations for the first rollout, etc. will be announced in the coming weeks.”

Lime launched in 2017 and has since recorded 11.5 million scooter and bike rides.

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Forget Watson, the Red Hat acquisition may be the thing that saves IBM

Published October 30, 2018

With its latest $34 billion acquisition of Red Hat, IBM may have found something more elementary than “Watson” to save its flagging business.

Though the acquisition of Red Hat  is by no means a guaranteed victory for the Armonk, N.Y.-based computing company that has had more downs than ups over the five years, it seems to be a better bet for “Big Blue” than an artificial intelligence program that was always more hype than reality.

Indeed, commentators are already noting that this may be a case where IBM finally hangs up the Watson hat and returns to the enterprise software and services business that has always been its core competency (albeit one that has been weighted far more heavily on consulting services — to the detriment of the company’s business).

Also read as IBM taps out on Watson as its growth engine and returns to basics ie financial engineering and distribution https://t.co/nD7gHyYhQf

— Sunil Rawat (@_sunilrawat) October 28, 2018

Watson, the business division focused on artificial intelligence whose public claims were always more marketing than actually market-driven, has not performed as well as IBM had hoped and investors were losing their patience.

Critics — including analysts at the investment bank Jefferies (as early as one year ago) — were skeptical of Watson’s ability to deliver IBM from its business woes.

As we wrote at the time:

Jefferies pulls from an audit of a partnership between IBM Watson and MD Anderson as a case study for IBM’s broader problems scaling Watson. MD Anderson cut its ties with IBM after wasting $60 million on a Watson project that was ultimately deemed, “not ready for human investigational or clinical use.”

The MD Anderson nightmare doesn’t stand on its own. I regularly hear from startup founders in the AI space that their own financial services and biotech clients have had similar experiences working with IBM.

The narrative isn’t the product of any single malfunction, but rather the result of overhyped marketing, deficiencies in operating with deep learning and GPUs and intensive data preparation demands.

That’s not the only trouble IBM has had with Watson’s healthcare results. Earlier this year, the online medical journal Stat reported that Watson was giving clinicians recommendations for cancer treatments that were “unsafe and incorrect” — based on the training data it had received from the company’s own engineers and doctors at Sloan-Kettering who were working with the technology.

All of these woes were reflected in the company’s latest earnings call where it reported falling revenues primarily from the Cognitive Solutions business, which includes Watson’s artificial intelligence and supercomputing services. Though IBM chief financial officer pointed to “mid-to-high” single digit growth from Watson’s health business in the quarter, transaction processing software business fell by 8% and the company’s suite of hosted software services is basically an afterthought for business gravitating to Microsoft, Alphabet, and Amazon for cloud services.

To be sure, Watson is only one of the segments that IBM had been hoping to tap for its future growth; and while it was a huge investment area for the company, the company always had its eyes partly fixed on the cloud computing environment as it looked for areas of growth.

It’s this area of cloud computing where IBM hopes that Red Hat can help it gain ground.

“The acquisition of Red Hat is a game-changer. It changes everything about the cloud market,” said Ginni Rometty, IBM Chairman, President and Chief Executive Officer, in a statement announcing the acquisition. “IBM will become the world’s number-one hybrid cloud provider, offering companies the only open cloud solution that will unlock the full value of the cloud for their businesses.”

The acquisition also puts an incredible amount of marketing power behind Red Hat’s various open source services business — giving all of those IBM project managers and consultants new projects to pitch and maybe juicing open source software adoption a bit more aggressively in the enterprise.

As Red Hat chief executive Jim Whitehurst told TheStreet in September, “The big secular driver of Linux is that big data workloads run on Linux. AI workloads run on Linux. DevOps and those platforms, almost exclusively Linux,” he said. “So much of the net new workloads that are being built have an affinity for Linux.”

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IBM to buy Red Hat for $34B in cash and debt, taking a bigger leap into hybrid cloud

Published October 30, 2018

After rumors flew around this weekend, IBM today confirmed that it would acquire open source, cloud software business Red Hat for $190 per share in cash, working out to a total value of $34 billion. IBM said the deal has already been approved by the boards of directors of both IBM and Red Hat but is still subject to Red Hat shareholder and regulatory approvals. If all goes as planned, the acquisition is expected to close in the latter half of 2019.

The deal is all about IBM, which has long continued to rely on its legacy server business, taking a bigger bet on the cloud, and very specifically cloud services that blend on-premises and cloud-based architectures — something that the two companies have already been working on together since May of this year (which now might be looked at as a test drive). Red Hat will be a distinct unit within IBM’s Hybrid Cloud team — which is already a $19 billion business for IBM, the company said — and it will continue to focus on open-source software. 

“The acquisition of Red Hat is a game-changer. It changes everything about the cloud market,” said Ginni Rometty, IBM Chairman, President and Chief Executive Officer, in a statement. “IBM will become the world’s number-one hybrid cloud provider, offering companies the only open cloud solution that will unlock the full value of the cloud for their businesses.”

The combined businesses will be able to offer software in services spanning Linux, containers, Kubernetes, multi-cloud management, and cloud management and automation, IBM said. IBM also added that together the companies will continue to build partnerships with multiple cloud providers, including AWS, Microsoft’s Azure, Google Cloud, Alibaba and others, alongside the IBM Cloud.

As Josh Constine notes here, it’s one of the biggest-ever tech acquisitions, and arguably the biggest that is dedicated primarily to software. (Dell acquired EMC for $67 billion, to pick up software but also a substantial hardware and storage business.)

While companies like Amazon have gone all-in on cloud, in many cases, a lot of enterprises are making the move gradually — IBM cites stats that estimate that some 80 percent of business workloads “have yet to move to the cloud, held back by the proprietary nature of today’s cloud market.” Buying Red Hat will help IBM better tap into an opportunity to address that.

“Most companies today are only 20 percent along their cloud journey, renting compute power to cut costs,” she continued. “The next 80 percent is about unlocking real business value and driving growth. This is the next chapter of the cloud. It requires shifting business applications to hybrid cloud, extracting more data and optimizing every part of the business, from supply chains to sales.”

On top of that, it will give IBM a much stronger footing in open source software, the core of what Red Hat builds and deploys today.

“Open source is the default choice for modern IT solutions, and I’m incredibly proud of the role Red Hat has played in making that a reality in the enterprise,” said Jim Whitehurst, President and CEO, Red Hat, in a statement. “Joining forces with IBM will provide us with a greater level of scale, resources and capabilities to accelerate the impact of open source as the basis for digital transformation and bring Red Hat to an even wider audience –  all while preserving our unique culture and unwavering commitment to open source innovation.”

While IBM competes against the likes of Amazon, the companies will see to remain partners with them with this acquisition. “IBM is committed to being an authentic multi-cloud provider, and we will prioritize the use of Red Hat technology across multiple clouds” said Arvind Krishna, Senior Vice President, IBM Hybrid Cloud, in a statement. “In doing so, IBM will support open source technology wherever it runs, allowing it to scale significantly within commercial settings around the world.”

IBM said that Red Hat will add to its revenue growth, gross margin and free cash flow within 12 months of closing.

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Google AI listens to 15 years of sea-bottom recordings for hidden whale songs

Published October 29, 2018

Google and a group of game cetologists have undertaken an AI-based investigation of years of undersea recordings, hoping to create a machine learning model that can spot humpback whale calls. It’s part of the company’s new “AI for social good” program that’s rather obviously positioned to counter the narrative that AI is mostly used for facial recognition and ad targeting.

Whales travel quite a bit as they search for better feeding grounds, warmer waters and social gatherings. But naturally these movements can be rather difficult to track. Fortunately, whales call to each other and sing in individually identifiable ways, and these songs can travel great distances underwater.

So with a worldwide network of listening devices planted on the ocean floor, you can track whale movements — if you want to listen to years of background noise and pick out the calls manually, that is. And that’s how we’ve done it for quite a while, though computers have helped lighten the load. Google’s team, in partnership with NOAA, decided this was a good match for the talents of machine learning systems.

These AI (we employ the term loosely here) models are great at skimming through tons of noisy data for particular patterns, which is why they’re applied to voluminous data like that from radio telescopes and CCTV cameras.

In this case the data was years of recordings from a dozen hydrophones stationed all over the Pacific. This data set has already largely been investigated, but Google’s researchers wanted to see if an AI agent could do the painstaking and time-consuming work of doing a first pass on it and marking periods of interesting sound with a species name — in this case humpbacks, but it could just as easily be a different whale or something else altogether.

Spectrograms of whale song, left, an unknown “narrow-band” noise, center, and the recorder’s own hard disk drive, right.

Interestingly, but not surprisingly in retrospect, the audio wasn’t analyzed as such — instead, the audio was turned into images it could look for patterns in. These spectrograms are a record of the strength of sound in a range of frequencies over time, and can be used for all kinds of interesting things. It so happens that they’re also well studied by machine learning and computer vision researchers, who have developed various means of analyzing them efficiently.

The machine learning model was provided with examples of humpback whale calls and learned how to identify them with reasonable accuracy in a set of sample data. Various experiments were conducted to suss out what settings were optimal — for instance, what length of clip was easy to process and not overlong, or what frequencies could be safely ignored.

The final effort divided the years of data into 75-second clips, and the model was able to determine, with 90 percent accuracy, whether a clip contained a “humpback unit,” or relevant whale sound. That’s not a small amount of error, of course, but if you trust the machine a bit you stand to save quite a bit of time — or your lab assistant’s time, anyway.

A second effort relied on what’s called unsupervised learning, where the system sort of set its own rules about what constituted similarity between whale sounds and non-whale sounds, creating a plot that researchers could sort through and find relevant groups.

Visualization of how the unsupervised model classified various sounds. The blue ones represent humpback calls.

It makes for more interesting visualizations but it is rather harder to explain, and at any rate doesn’t seem to have resulted in as useful a set of classifications as the more traditional method.

As with similar applications of machine learning in various scholarly fields, this isn’t going to replace careful observation and documentation but rather augment them. Taking some of the grunt work out of science lets researchers focus on their specialties rather than get bogged down in repetitive stats and hours-long data analysis sessions.

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