Monthly Archives: February 2017

2016 was supposed to be the year the tech bubble finally burst.

Much like the dot-com bubble of the early 2000s an industry implosion marked by high-profile flops such as online grocery delivery startup Webvan and pet supplies retailer Pets.com skeptics pointed to less VC funding in 2016, stratospheric valuations including Ubers $69 billion, the sales of once-pricey companies such as One Kings Lane, and sky-high rental and real estate prices.

And contrary to tech insiders who largely remain bullish on the industry, some even saw smaller signs of a bubble in the hours-long bumper-to-bumper traffic on the US-101, a highway that meanders its way down the peninsula to tech-laden cities such as Menlo Park, San Jose and Mountain View.

But after more than six years in Silicon Valley collectively, Im convinced there isnt one big bubble these days, but rather a series of smaller bubbles within tech that balloon and swell until they burst, taking with them the droves of copycat derivatives and poorly managed companies all trying to capitalize on the latest, frothiest trend.

Ask just about any venture capitalist at this moment, and theyll tell you theyre seeing a glut of artificial intelligence and machine learning startups flow their way angling for cash, employing increasingly complex algorithms across a wide range of industries.

While some of these new companiesmay fulfill actual needs, there may simply be more AI startups than the world needs.

The pets.com sock puppet dog stars in a commercial for the company, Los Angeles, California, January 11, 2000. Photo by Bob Riha/Liaison/Getty Image

Of course, some AI startups are more promising than others. Andreessen Horowitz general partner Vijay Pande told Yahoo Finance he is particularly bullish on companies such as Freenome, which the firm invested in last June. The Palo Alto-based startup uses machine learning to help detect different types of cancers from a blood test rather than from a tissue sample a process that detects cancer long before more traditional methods can. Another startup Pande invested in, the health tech startup Cardiogram, is promising because it makes sense of and analyzes large amounts of user data to provide actionable insights that could ultimately save lives.

SomeA.I. ventures are trying to shake up other long-standing industries, like the San Carlos, Calif.-based Farmers Business Networks,a social network for, well, farmers, that relies on machine learning to improve data results around seed performance and pricing. And there are many, many more.

While its too early to tell which of those startups will evolve into viable businesses and which wont, its relatively easy to look back over the last decade now to see past micro-bubbles for what they actually were.

Alex Mittal, CEO and co-founder of the FundersClub, an online VC firm which invests in promising tech startups, agrees Silicon Valley has found itself swept up in macro-trends over the years that come and go in predictable cycles.

Every time theres a focus on a technology thats new, it gets overhyped, and the hype reaches an extreme, Mittal told Yahoo Finance. The pendulum always seems to swing too far, and theres some sort of correction. Sometimes, it literally was just hype. Theres no substance, and then it goes away. But sometimes, theres something really there.

The 2008 financial crisis, interestingly, marked the first micro-bubble, marked by the sharing economy, a business model based on the idea that assets or services are shared between people through the internet or mobile. Airbnb, founded in 2008, singlehandedly legitimized the idea of couch-surfing as a hotel alternative, by easily letting people rent out a room, an apartment or a home; Uber in 2009 upended the crusty, old taxi industry by creating a network of private drivers reachable with just a few easy taps on the smartphone.

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But while Airbnb and Uber have become bona fide global businesses, many more sharing economy upstarts failed to catch on. Remember the Uber copycat Sidecar? Shut down in 2015, because Uber and Lyft had more money and an easier-to-understand user experience.

How about laundry delivery ventures Prim and Washio? Shuttered in 2014 and 2016, respectively, due to low profit margins and high infrastructure costs. Even businesses like Homejoy, an online marketplace for cleaning services, hit the skids despite many a venture capitalist crowing about what a promising business it was apparently due to a lack of repeat customers and slew of lawsuits.

Washio was the victim of another micro bubble.

On the heels of the sharing economy bubble came a slew of e-commerce startups like online design store Fab.com. It burned through a significant chunk of the $325 million it raisedin aggressive attempts to expand globally, acquiring similar sites in Germany and England, before a spectacular crash-and-burn that few in Silicon Valley, including its investors, will forget anytime soon.

Meanwhile, once-promising home furnishings site One Kings Lane, which failed to differentiate itself enough from the glut of flash-sale sites, sold for just $12 million last August to Bed Bath & Beyond a serious markdown from its $900 million valuation of yesteryear and online furniture retailer Dot & Bo used up its $20 million in funding before shuttering last September.

The most recent micro-bubble to burst? On-demand food delivery startups. No less than a dozen food delivery startups have shuttered over the last 18 months, with names like Bento, Spoonrocket, Din, Kitchit, Kitchen Surfing, and the creatively-named Take Eat Easy. Others like Munchery, Zesty and Sprig, trudge on, but with considerably downsized workforces. Because, while people certainly enjoy good dining, there were too many startups for San Francisco locals for them to keep track of and not enough interested mouths to feed. Indeed, Din founders Emily Olson and Rob LaFave pointed to an overly crowded market as a key reason for closing the startup in a postmortem interview with SF Eater in October.

Many of the venture capitalists and founders Ive spoken to in recent months are hopeful that this latest boom in A.I. and machine learning startups isnt part of another micro-bubble in the way many sharing economy and e-commerce startups came and went in the past, largely because these technologies can ostensibly benefit and improve any industry, from health care to agriculture to consumer-focused virtual assistants. (Hello, Alexa.)

A.I. is probably more accessible than it has ever been before, contended Peter Cahill,an authority on A.I., who has spent the last 15 years studying speech technology and neural networks from Dublin, Ireland.Its easier for companies to see the clear benefits from it because technology has largely caught up.

Maybe theyre right this time, or maybe the Farmers Business Networks of the world will eventually join the startup graveyard, alongside Fab.com, Homejoy and so many others. But as Mittal points out, this almost blinding sense of optimism that any startup with a good idea can succeed is what makes Silicon Valley unique and, dare I say it, innovative. Because for every 100 startups, 10 of them may become successful, and perhaps one has the potential to become the next transformative company like Facebook (FB).

Its a large part of the reason Im still here, Mittal confesses, with a sheepish grin.

No doubt many in Silicon Valley would agree.

JP Mangalindan is a senior correspondent covering the intersection of business and technology.

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Why AI could be Silicon Valley's latest 'micro bubble' - Yahoo Finance - Yahoo Finance

The company announced that it is building the worlds largest artificial intelligence platform

At *.ai Intelligent Cloud, a conference hosted by Microsoft India in Bengaluru on Monday, the company said that Big Data, Cloud, and intelligence have changed the way machines compute services for human beings. It also announced that it was building the worlds largest artificial intelligence (AI) platform.

"Cognitive services will change IT applications in the future. Services can become intelligent with machine learning and we are providing APIs to startups for computer applications like vision, speech, language, knowledge and search," says Sandeep Alur, Microsoft Lead Evangelist.

The company also positioned itself as a champion of open source technologies, with over 16,000 contributions made on GitHub, an open source internet hosting service. Large corporate like Google are in the game too. They joined the .Net Foundation technical steering group, which was launched by Microsoft.

Microsoft, in return, joined the Linux Foundation. While this global exchange of knowledge is well-founded, today every one wants to know what AI is all about.

Analysts at Gartner tell YourStory that today most neural networks are still in the realm of machine learning, which means outcomes can be predictive. Computer science experts will say that AI comes with reasoning power, which means machines can fool you into believing they are human.

That said, several software engineers are going after building computers that can create predictive outcomes for services. Say, a machine can tell when a part could fail and will inform the customer about going to the dealership to replace the part. Let us also say you call a BPO and a chatbot using voice technologies, which will guide you through a query better than any human. Says Alur of Microsoft,

"Today, building a bot means maintaining several source codes. But we have created a framework for bots with one source code."

Research firm Markets&Markets says the AI market could be $16 billion by 2022.

Bot frameworks can change the way BPOs function and change their outcomes.

However, the point is that while all these frameworks make it easy with a lot application channels, saying that we are in the realm of AI is a wrong argument. However, the push that Microsoft offers, to go towards AI with machine learning, is something to watch out for.

Let's look at the numbers. If we look at all the system integrators, starting from Accenture to Infosys to TCS to Wipro, their revenues from platforms that offer AI or machine learning is less than 10 percent.

"Data is critical and we can build models that can become critical for predictive planning," says Anish Basu Roy, CEO of Shotang.

Several startups that YourStory spoke to believed that machine learning was today called AI. "Everything that is F of X is considered AI, when all we are building is an intelligent machine," said founders of a couple of startups who did not want to be named.

Representatives of the Indian startup ecosystem in the room were extremely robust. Over 200 of them were present and most of them were in the realm of data analytics, cognitive sciences and predictive maintenance. Somehow, the feeling was that they were here to witness Satya Nadella's talk with Nandan Nilekani.

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Microsoft India projects itself as open source champion, says AI is the next step - YourStory.com

"In the early days, we were all amused by the sheer novelty of A.I. Now with maturity, our users expect more concrete results with almost no errors. Our engineers have built arbitrage mechanisms that provide more confidence than any individual A.I. system could. Concretely, this means less work for our users but more work for the machines. That's ok, though, as the machines don't have to drive the kids back from school," said Karl Facredyn CEO of Orange Logic.

How it works:

Pass One: Detect The Content

The first pass of A.I. uses two separate machine learning instances. Each instance undergoes its own training and will interpret and produce results for an asset independently of the other machine.

Pass Two: Arbitrage Results

A third A.I. arbitrages the results from the first pass and only keeps the most accurate results of the two previous A.I.'s.

About Orange Logic

Established in 2000, Orange Logic initially operated as a software research company on a mission to innovate approaches in multiple fields including Digital Asset Management. Today, Orange Logic provides a premier Digital Asset Management solution CORTEX | DAM for any team, national or global, looking to efficiently manage and scale its digital media libraries.

To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/orange-logic-deploys-a-second-generation-of-machine-learning-ai-for-digital-asset-management-300410174.html

SOURCE Orange Logic

http://www.orangelogic.com

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Orange Logic Deploys a Second Generation of Machine Learning AI for Digital Asset Management - PR Newswire (press release)

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When The Computer Is You: The Rise Of Proxy AI Forbes In 1945, Vannevar Bush published As We May Think. In it he proposed a Memex, a massive microfilm storage device where users could navigate between documents to concepts throughout the database. His concept directly inspired the invention of ...

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If AI is rolled out to rapidly and irresponsibly its benefits could actually cause far reaching consequences for millions.

AI has been named as one of the most importantemerging trendsin business technology for 2017 in a report by Accenture, but are we ready for it?

The report, Technology Vision, is a yearly look atthe biggest trends in business for the coming year. The 2017 iteration has named AI as one of the principle changes that will shape the landscape in business for years to come.

AI itself has become increasingly more prevalent in the world and as we move closer towards self driving cars and responsive voice commands for our smart homes, its importance cannot be understated. The more integrated artificial intelligence becomes in our daily lives, the more businesses should strive to adopt it into their operations, though they should be mindful of its potential consequences.

Accenture believe thatAI has the potential to become a spokesperson for a business, even becoming more recognisable than the brand itself. As AI replaces interfaces and reshapes interactions with customers it will become a representative of businesses image as a whole.

Amazon Echo is a great example. Now used in more than 3 million homes, the Smart Speaker utilises an AI known as Alexa in an effort to streamline home living. The device is capable of enhancing customer experiences by giving access to weather and traffic reports as well as offering the ability to order much of Amazons listings just by talking to it.

Paul Daugherty, Accenture chief technology & innovation officer said: As technology transforms the way we work and live, it raises important societal challenges and creates new opportunities. Ultimately, people are in control of creating the changes that will affect our lives, and were optimistic that responsive and responsible leaders will ensure the positive impact of new technologies.

The Technology Vision Survey of over 5,000 IT and business executives revealed that over 79% believe that AI will help accelerate technology adoption, with a further 85% stating that they would be making extensive investments into the technology over the next three years.

Current examples of AI being utilised outside of consumer applications include the Rhizabot, an AI program which can translate complex business analysis questions, alleviating the need to create simplified and easily translatable phrases that may not be sufficient. In agriculture also, farmers have been using AI crop management tools that allow machines to learn how best to tend crops, whether through increased water and fertiliser supply or removing sprouts that will hinder the growth of others.

Accenture estimates that in 5 years customers will be less impressed with brands and place much more stock in how well the AI interface functions. In 7 years most interfaces will have moved beyond screens and become integrated into daily tasks, and in 10 years they predict that AI assistants will be so intertwined with day to day tasks that they will maintain constant productivity through outlets such as creating video summaries immediately aftermeetings.

However, this rapid integration and expansion of AI throughout the business world could have a serious domino effect. For instance, if certain positions can be phased out in favour of increasingly more advanced AI, it has the potential to create serious economic inequality. Because theAIrequires no compensation for its time, the potential profit for its service will be disseminated throughout a smaller number of people.

Recently, Bill Gates, founder of Microsoft, suggested that should robots supplant humans in the workplace they should be taxed as a human would.

In an interview with Quartz, Gates said:Right now, the human worker who does, say, $50,000 worth of work in a factory, that income is taxed and you get income tax, Social Security tax, all those things. If a robot comes in to do the same thing, youd think that wed tax the robot at a similar level.

The billionaire philanthropist believes that the income tax made from robots could be used to support social systems and train others in more skilled labour in response to growing automation.

As more and more tasks become automated it seems inevitable that an AI could eventually be used to replace a customer service line, or a call centre. Amazons Alexa is just one of many AIs that use continual physical interactions and cloud learning to improve its own speech patterns and usability constantly. During initial tests Alexas response time was three seconds, too long for a sufficient conversation, since then Amazon has managed to reduce that time to under 1.5 seconds.

Will we see rapid growth in unemployment if Artificial Intelligence is rolled out irresponsibly? If self driving technology can ever be applied to heavy goods vehicles it could very well put millions of truck drivers out of work worldwide.

Emma McGuigan at Accenture said that lorry drivers are a long way from being replaced, so that is not an immediate concern. She believes that AI will cause a disruption in the business world, but that disruption will be a net positive. Accenture introduced AI into its India business but rather than leave many unemployed it actually allowed 20,000 people to be redeployed to other tasks where a human touch is necessary,

She said: I dont think the pace of AI will affect work, I think it will actually increase it.

For many the concept of integrated Artificial Intelligence seems to be a question of when and not if, so as the business world moves forward its important to ensurethat this technology is implemented in a safe and secure way that maximises benefit for businesses, employee, and consumer alike.

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NVIDIA's Accelerated Computing Platform To Power Japan's Fastest AI Supercomputer Forbes Tokyo Tech is in the process of building its next-generation TSUBAME supercomputer featuring NVIDIA GPU technology and the company's Accelerated Computing Platform. TSUBAME 3.0, as the system will be known, will ultimately be used in tandem with ... and more »

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NVIDIA's Accelerated Computing Platform To Power Japan's Fastest AI Supercomputer - Forbes