Tag Archive for Artificial intelligence

Motor City v. Silicon Valley

– Updated 03-30-2018 – Business Insider reports that Silicon Valley darling Tesla shares have collapsed almost 6% since January 1 on a string of critical reports about the company’s ability to keep up healthy production levels and meet delivery expectations for its new mass-market Model 3 sedan.

Motor City v. Silicon ValleyBack in April, the tech sector was leaping for joy when Tesla’s stock market valuation passed Ford and GM. Rumors abound in Silicon Valley that Tesla is the future of transportation and Elon Musk is the king of cars because they took more orders for cars that did not burn up or crash out of control. In 2016 Tesla delivered only 76,000 vehicles. Ford sold nearly 1 million F-Series trucks in 2016.

Ford and GMDespite the happy dances in Silicon Valley, which fancy itself as the logical successor to Detroit as the capital of American innovation new research says not so fast. The west coast upstartsUber, Google (GOOG), and Tesla (TLSA) — still have a lot of catching up to do when it comes to outpacing Michigan manufacturers. The Verge points us to Navigant Research, whose newly released “leaderboard” report ranks autonomous vehicle players not just on their ability to make a car drive itself, but on their ability to bring that car to the mass market. 

Navigant Research scored 18 companies working on self-driving technology on 10 different criteria related to strategy, manufacturing, and execution. The report combined all that into an overall score to get a sense of who’s ahead and who’s not. General Motors (GM) and Ford (F) are currently leading the pack, with Daimler and Renault-Nissan close behind. Those four companies make up Navigant’s “leader” category. In other words, when you climb into your first self-driving car in 2021, it will almost certainly be built by one of those four companies.
Navigant Research Leaderboard: Automated Driving Vehicles

Most everyone else is in the “contender” category. This includes car companies like BMW, PSA, Hyundai, Toyota, Tesla, and Volkswagen; suppliers like Delphi and ZF; and tech firms like Alphabet’s Waymo. Further down the list, in the “challengers” category, are companies like Honda, nuTonomy, Baidu, and Uber.

Detroit is beating Silicon ValleyGM Assembly line

Sam Abuelsamid, a senior research analyst at Navigant and one of the authors of the report, told the Verge the reason Detroit beating Silicon Valley so badly in this all-too-crucial race to get autonomous vehicles on the road is because of experience. He says, Silicon Valley, “ …. will have to do deals with someone to get actual vehicles.”

Alphabet’s Waymo, scores top marks for technology but drags in the production strategy and sales, marketing, and distribution buckets. The company plans to work with legacy automakers to put its tech in cars, but has not yet struck any major deals. Mr. Abuelsamid detailed on an email with the Verge that Waymo is in the best position of the contenders.

Waymo logoThey have almost every piece of this—except the product strategy … Waymo has what is arguably the best technology right now, although they probably aren’t that far ahead of the leading [original equipment manufacturers] but they will have to do deals with someone to get actual vehicles”

Despite Uber’s high profile, a recent study showed that only 15% of U.S. consumers have tried a ride-hailing app like Uber. Uber also has a safety problem – Uber drivers have been charged with murder and violent crimes against their customers.  In the Navigant research, Uber wallows near last place thanks to low grades for distribution, product portfolio, and staying power—and because makes Uber makes neither cars nor money. In fact, its key strength—that it already operates a global fleet of shared vehicles—may not be enough here. “It’s a lot easier for the company that actually has the infrastructure to create vehicles to recreate what Uber’s done, than the other way around,” Mr. Abuelsamid says.

Scale matters in the auto industry.

The Navigant analyst explained scale matters in the auto industry.

All the little [Silicon Valley] startups may have some interesting ideas, but they don’t have the resources to produce something sufficiently robust to be commercially viable. If they have something good to offer, their best bet is an acquisition

Mergers and acquistionsThe “legacy automakers” have engaged in mergers and acquisitions and early maneuvering in the autonomous vehicle arena as Mr. Abuelsamid stated. The report predicts that big companies will buy little startups to leverage their technology and expertise to round out the much larger-scale enterprise of developing, testing, validating, producing, and distributing self-driving cars.

Wired says Ford and GM both score in the low to mid 80s on the technology front; it’s their old-school skills that float them to first and second place. They’ve each spent more than a century developing, testing, producing, marketing, distributing, and selling cars. Plus, each has made strategic moves to bolster weak points.

Chevy BoltGM recently acquired Cruise Automation, a San Francisco-based autonomous vehicle technology maker in a deal valued at more than $1 billion. GM said the acquisition will allow it to “accelerate” its autonomous vehicle development efforts.

Ford has announced an investment of $1 billion over the next five years in Argo AI, a startup run by Carnegie Mellon roboticists and engineers who really know their artificial intelligence stuff.

Waymo Chryslet PacificaFiat Chrysler has partnered with Alphabet to jointly test autonomous technology in Pacifica minivans, and Alphabet is opening a 53,000 square foot self-driving car development center near Detroit in Novi, MI.

GM has invested $500 million in ride-sharing provider Lyft to beef up its ridesharing service. In the “long-term strategic alliance,” the companies will work on what they call “on-demand autonomous vehicles.” For now, the deal means GM cars will be the “preferred” vehicle used by Lyft drivers who rent their cars in various U.S. cities. Those vehicles will tap into GM’s OnStar service, while GM and Lyft promised “personalized mobility services and experiences,” but did not elaborate.

Ford invested $75 million iin LiDAR maker VelodyneFord, meanwhile, recently announced a $75 million investment in LiDAR maker Velodyne, to “quickly mass-produce a more affordable automotive LiDAR sensor” so the company can launch a fleet of self-driving ride-sharing cars by 2021

Ford has also acquired SAIPS, an Israeli machine learning firm to further strengthen its ability in artificial intelligence and computer vision. SAIPS has developed algorithmic solutions in image and video processing, deep learning, signal processing and classification. This expertise will help Ford autonomous vehicles learn and adapt to the surroundings of their environment

Ford announced that it would take part in a $6.6 million seed funding round for Civil Maps to further develop high-resolution 3D mapping capabilities. This provides Ford another way to develop high-resolution 3D maps of autonomous vehicle environments. Ford has also agreed to acquire Chariot, an on-demand shuttle service based in San Francisco.

Mr. Abuelsamid predicts that early on,  you probably won’t be buying a self-driving car at a dealership, but rather riding in one that you hail through an app-based service like Uber or Lyft. These vehicles will be part of a fleet owned by a manufacturer, like Ford or GM. Fleet ownership will help manufacturers manage the issues self-driving vehicles are likely to encounter early on, like insurance for the inevitable accidents. Navigant’s Abuelsamid says

With all of that in mind, it’s far easier for a manufacturer to replicate the sort of logistics platform that Uber or Lyft have than it is for those companies to invest in and create the development, manufacturing, and service infrastructure that [original equipment manufacturers] have

Mr. Abuelsamid noted that Tesla ranked pretty far down the “contender” because Elon Musk’s company is “lacking in quality, distribution, financial stability, and their [Autopilot] 2.0 hardware will never be more than limited Level 4-capable (PDF) at best.” In other words, Musk would be advised not to start gloating about his company being valued higher than the OG’s Ford and GM quite yet.

Related articles

 

Ralph Bach has been in IT long enough to know better and has blogged from his Bach Seat about IT, careers, and anything else that catches his attention since 2005. You can follow him on LinkedInFacebook, and Twitter. Email the Bach Seat here.

Chatbots Are Evolving

The momentum behind chatbots is growing. American Banker reports that major banks are actively experimenting with chatbots. Chatbots is short for chat robot, a computer program that simulates human conversation, or chat, through artificial intelligence. Typically, a chatbot will communicate with a real person, but applications are being developed in which two chatbots can communicate with each other. Chatbots are used in applications such as e-commerce customer service and call centers.

decide how to use chatbotsBanks trying to decide how to use chatbots include Ally, BBVA, Bank of America, Barclays, Capital One, Societe General/a>, and USAA.  A survey conducted by Personetics found that 87% of bankers say they plan to do something with chatbots by 2020.

Penny Crosman, the author reports that a growing number of vendors are offering prefab chatbots trained with documents, data, and conversations about financial products and topics. Some are intended to replicate the interaction with a human, while others are styled more like workhorses. The author describes four types of chatbots being used today.

Types of chatbots

The conversationalistKai is the Chatbot from Kasisto. Kasisto is a spinoff of the research lab, SRI International. SRI developed the first public Artificial Intelligence (AI) Siri, which Apple purchased in 2010 for use in the iPhone.

The conversational chatbotSearchCIO defines AI as the simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, and self-correction. Particular applications of AI include expert systems, speech recognition, and machine vision.

Siri knows a lot — it’s very broad but very shallow,” Zor Gorelov, CEO and co-founder of Kasisto. A group of SRI researchers realized a financial services chatbot would have to be narrow and deep and started working on one. BBVA approached the group in 2009. BBVA was looking for human-like interactions from a chatbot, and the two organizations partnered to create a virtual banking assistant. Mr. Gorelov said the SRI researchers “interviewed people across the banking universe at BBVA … transcribed tens of thousands of calls.”

Kasisto logoA staff of full-time writers called “artificial intelligence interaction designers” produces dialogues for Kai. American Banker says they also constantly monitor the behavior and user interactions. General banking knowledge has also been embedded. “You can ask Kai questions about CDs, IRAs, credit scores — it’s the smartest banker you can imagine from a customer onboarding point of view: how do I open an account, what document do I need?” Kasisto’s Gorelov says there are 10 to 11 messages exchanged between Kai and users during an average session,

The article noted that Kai is used by digibank, a mobile-only bank launched in India by DBS Bank in Singapore, and it’s being piloted by the Royal Bank of Canada.

The doer chatbotThe DoerPersonetics has built a library of customer insights for its chatbots. Its builders fed the chatbot technology financial services information for five years and fueled it with unsupervised and supervised machine learning, natural language understanding, logic inference, and associative knowledge according to AB.

While other chatbots might aim to simulate a real conversation, Personetics tries to make it clear the customer is not dealing with a human to avoid potential confusion.

Eran Livneh, vice president of Personetics explained the chatbot is akin to an employee who understands banking and serving customers really well. The chatbots can walk customers through steps, provide predictive messages and behavior insights, and automatically perform tasks like money management.

Personetics logoSo though they can “chat” with customers, they’re primarily designed to actually do things for them. Ally Bank and Societe Generale use chatbots by  Personetics.

The linguist – Montreal-based software company North Side, specializes in giving its chatbot, VerbalAccess, a precise understanding of language, whether spoken or typed, through natural language processing technology.

The article notes that North Side didn’t start out in banking. Originally it created a video game that lets players communicate with characters. “That’s how we made our natural language understanding pipeline robust,” said Eugene Joseph, North Side’s CEO.

The linguist chatbotNorth Side doesn’t try to glean insights from analyzing customer behavior. Instead, it takes commands and acts on them, such as making a payment or displaying a transaction. If a user asks, “What have I spent on coffee in the last month?” North Side’s chatbot will understand the question and translate it to an API call that will extract the answer automatically. It would make the same calls that might be made by a mobile banking app or online banking site, but with the added ability to translate from the imprecise way a human might ask something to language the software can understand..

The chatbot is trained to clarify users’ questions. “If what is said is incomplete, it will elicit the missing information,” Mr.Joseph said. “That’s very important because people speak in an incomplete way. We know what to ask for.”

The Teller – Sidharth Garg began working on his chatbot, Teller, while at Columbia Business School. He told AB,I wanted to use the recent advances in natural language processing and the opening of messaging platforms to help people learn the basics of personal finance.

The Teller chatbotTo feed Teller the information to answer customers’ questions, he went through blogs and personal finance books, attempting to answer every general personal finance question he could think of. Mr. Garg explained the goal was to make retirement options easy to understand. He “…put together Buzzfeed-style graphics that explain the different types of retirement accounts into something someone could understand on their mobile device.

He decided to focus on the business-to-consumer market. “People are more inclined to chat with a banking assistant that comes from an institution they already trust,” Mr. Garg told the author. “They already have a captive audience of customers and they would also allow for easy integration with their bank accounts.

Recently, he’s been running a pilot program with Brooklyn Cooperative Federal Credit Union that has provided more real-world data to train the chatbot. For now, the bot is answering only the most general questions for the credit union’s customers. Eventually, the plan is to integrate the chatbot with the credit union’s back-end system, to let it answer questions specific to customers’ accounts.

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I have written about chatbots a couple of times on the Bach Seat. Google, Facebook, Microsoft, and even Pizza Hut are experimenting with bot-to-human interactions.  Chatbots will get smarter as more people keep using them, and as developers perfect the tools to turn the software into what people want and need. Like Personetics’ Livneh said, “Customers generally like things that help them with the day-to-day activities.”  Chatbots will also cost jobs.

 

Ralph Bach has been in IT long enough to know better and has blogged from his Bach Seat about IT, careers, and anything else that catches his attention since 2005. You can follow him on LinkedIn, Facebook, and Twitter. Email the Bach Seat here.

Chatbot Risks

Chatbot RisksChatbots are the latest rage on social media. As Time explained, they have been around since the 1960s. That’s when MIT professor Joseph Weizenbaum created a chatbot called ELIZA. Chatbots found a home on desktop messaging clients like AOL Instant Messenger. Chatbots went dormant as messaging transitioned away from desktops and onto mobile devices.

Sophiscated botBut they’re poised for a resurgence in 2016. There are two reasons for this. First, artificial intelligence and cloud computing has gotten better thanks to improvements in machine learning. Second, bots could be big money.

Tech titans have chatbots on social media

All the tech titans have released social bots on the web; Apple’s (AAPL) Siri, Facebook’s (FB) “bots on Messenger“, Google’s (GOOG) Allo, and Microsoft’s (MSFT) ill-fated Tay. They believe there’s a buck to be made here, and they’re scrambling to make sure they don’t get left out.

Social botThe July issue of the Communications of the ACM included an article, “The Rise of Social Bots,” which lays out social bots’ impact on online communities and society at large. The authors define a social bot as a computer algorithm that automatically produces content and interacts with humans on social media, trying to emulate and possibly alter their behavior.

The Business Insider published this infographic about the social bot ecosystem.

Business Insider infographic

Chatbots can be deceptive

The ACM article argues that social bots populate techno-social systems; they are often benign, or even useful, but some are created to harm by tampering with, manipulating, and deceiving social media users. The article offers several examples of how social bots can be a hindrance. The first example involves the Twitter (TWTR) posts around the Boston Marathon bombing. The researcher’s analysis found that social bots were automatically retweeting false accusations and rumors. The researchers argue that forwarding false claims without verifying the false tweets granted the false information more influence.

bots can artificially inflate political candidatesThe ACM article also discusses how social bots can artificially inflate political candidates. During the 2010 mid-term elections some politicians used social bots to inject thousands of false tweets to smear their opponents. This type of activity puts the integrity of the democratic process at risk. These types of attackers are also called astroturfing, or twitter-bombs.

Anti-vaxxer chatbots

The article offers another example of the use of social bots to influence an election in California. During the recent debate in California about a law on vaccination requirements there appears to be widespread use of social bots by opponents to vaccinations. This social bot interference puts an unknown number of people at risk of death or disease.

bot provoked stock market crashGreed is the most likely use of social bots. One example from the article is the April 2013 hack of the Twitter account of the Associated Press. In this case, the Syrian Electronic Army used the hacked account to posted a false statement about a terror attack on the White House which injured President Obama. This false story provoked an immediate $136 Billion stock market crash as an unwarranted result of the widespread use of social bots to amplify false rumors.

Chatbots manipulate social media reality

Research has shown that human emotions are contagious on social media. This means that social bots can be used to artificially manipulate social media users’ perception of reality without being aware they are being manipulated. The article says the latest generation of Twitter social bots has many “human-like” online behaviors that make it difficult to separate bots from humans. According to the authors, social bots can:

  • Search the web to fill in their profiles,
  • Post pre-collected content at a defined time
  • Engage in conversations with people,
  • Infiltrate discussions and add topically correct information.

Some bots garner attention.Some bots work to gain greater status by searching out and following popular or influential users or taking other steps to garner attention. Other bots are identity thieves, adopting slight variants of user names to steal personal information, picture, and links.

Strategies to thwart bad chatbots

The authors review several attempts to thwart these growing sophisticated bots.

1. Innocent-by-association – This theory measured the number of legitimate links vs. the number of social bots (Sybil) links a user has. This method was proven to be flawed. Researchers found that Facebook users are pretty indiscriminate when adding users. The article says that 20% of legitimate Facebook users accept any friend request and 60% accept friend requests with only one contact in common.

2. Crowdsourcing – Another approach to stop social bots is crowdsourcing. The crowdsourcing approach would rely on users and experts reviewing an account. The reviewers would have to reach a majority decision that the account in question was a bot or legit. The authors pointed out some issues with crowdsourcing.

  • It will not scale to large existing social networks like Facebook or Twitter.
  • “Experts” need to be paid to check accounts.
  • It exposes user’s personal information related to the account to unknown users and “experts.”

3. Feature-based detection is the third method the researchers noted by the authors. Feature-based bot detection uses behavior-based analysis with machine learning to separate human-like behavior from bot-like behavior. Some of the behaviors that these types of applications include:

  • The number of retweets.
  • Age of account.
  • Username length.

4. Sybil until proven otherwise – The Chinese social network RenRen uses the fourth method noted by the author. This network uses a “Sybil until proven otherwise” approach. According to the article, this approach is better at detecting unknown attacks, like embedding text in graphics.

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Use your brainWhile people’s ability to critically assimilate information, is beyond technology, the authors call for new ways to detect social bot-generated spam vs. real political discourse.

The researchers speculate there will not be a solution to the social bot problem. The more likely outcome is a bot arms race, like what we are seeing in the war on SPAM and other malware.

Related articles
  • Man vs. Machine: What do Chatbots Mean for Social Media? (blogs.adobe.com)

 

Ralph Bach has been in IT long enough to know better and has blogged from his Bach Seat about IT, careers, and anything else that catches his attention since 2005. You can follow him on LinkedInFacebook, and Twitter. Email the Bach Seat here.