Posted In:Robotics Archives - AppFerret
A revolution in warfare where killer robots, or autonomous weapons systems, are common in battlefields is about to start.
Both scientists and industry are worried.
The world’s top artificial intelligence (AI) and robotics companies have used a conference in Melbourne to collectively urge the United Nations to ban killer robots or lethal autonomous weapons.
An open letter by 116 founders of robotics and artificial intelligence companies from 26 countries was launched at the world’s biggest artificial intelligence conference, the International Joint Conference on Artificial Intelligence (IJCAI), as the UN delays meeting until later this year to discuss the robot arms race.
Toby Walsh, Scientia Professor of Artificial Intelligence at the University of New South Wales, released the letter at the opening of the opening of the conference, the world’s pre-eminent gathering of experts in artificial intelligence and robotics.
The letter is the first time that AI and robotics companies have taken a joint stand on the issue. Previously, only a single company, Canada’s Clearpath Robotics, had formally called for a ban on lethal autonomous weapons.
In December 2016, 123 member nations of the UN’s Review Conference of the Convention on Conventional Weapons unanimously agreed to begin formal talks on autonomous weapons. Of these, 19 have already called for a ban.
“Lethal autonomous weapons threaten to become the third revolution in warfare,” the letter says.
“Once developed, they will permit armed conflict to be fought at a scale greater than ever, and at timescales faster than humans can comprehend.
“These can be weapons of terror, weapons that despots and terrorists use against innocent populations, and weapons hacked to behave in undesirable ways. We do not have long to act. Once this Pandora’s box is opened, it will be hard to close.”
Signatories of the 2017 letter include:
- Elon Musk, founder of Tesla, SpaceX and OpenAI (US)
- Mustafa Suleyman, founder and Head of Applied AI at Google’s DeepMind (UK)
- Esben Østergaard, founder & CTO of Universal Robotics (Denmark)
- Jerome Monceaux, founder of Aldebaran Robotics, makers of Nao and Pepper robots (France)
- Jü rgen Schmidhuber, leading deep learning expert and founder of Nnaisense (Switzerland)
- Yoshua Bengio, leading deep learning expert and founder of Element AI (Canada)
Walsh is one of the organisers of the 2017 letter, as well as an earlier letter released in 2015 at the IJCAI conference in Buenos Aires, which warned of the dangers of autonomous weapons.
The 2015 letter was signed by thousands of researchers working in universities and research labs around the world, and was endorsed by British physicist Stephen Hawking, Apple co-founder Steve Wozniak and cognitive scientist Noam Chomsky.
“Nearly every technology can be used for good and bad, and artificial intelligence is no different,” says Walsh.
“It can help tackle many of the pressing problems facing society today: inequality and poverty, the challenges posed by climate change and the ongoing global financial crisis. However, the same technology can also be used in autonomous weapons to industrialise war.
“We need to make decisions today choosing which of these futures we want. I strongly support the call by many humanitarian and other organisations for an UN ban on such weapons, similar to bans on chemical and other weapons,” he added.”
Ryan Gariepy, founder of Clearpath Robotics, says the number of prominent companies and individuals who have signed this letter reinforces the warning that this is not a hypothetical scenario but a very real and pressing concern.
“We should not lose sight of the fact that, unlike other potential manifestations of AI which still remain in the realm of science fiction, autonomous weapons systems are on the cusp of development right now and have a very real potential to cause significant harm to innocent people along with global instability,” he says.
“The development of lethal autonomous weapons systems is unwise, unethical and should be banned on an international scale.”
An Open Letter to the United Nations Convention on Certain Conventional Weapons
As companies building the technologies in Artificial Intelligence and Robotics that may be repurposed to develop autonomous weapons, we feel especially responsible in raising this alarm. We warmly welcome the decision of the UN’s Conference of the Convention on Certain Conventional Weapons (CCW) to establish a Group of Governmental Experts (GGE) on Lethal Autonomous Weapon Systems. Many of our researchers and engineers are eager to offer technical advice to your deliberations. We commend the appointment of Ambassador Amandeep Singh Gill of India as chair of the GGE. We entreat the High Contracting Parties participating in the GGE to work hard at finding means to prevent an arms race in these weapons, to protect civilians from their misuse, and to avoid the destabilizing effects of these technologies.
We regret that the GGE’s first meeting, which was due to start today, has been cancelled due to a small number of states failing to pay their financial contributions to the UN. We urge the High Contracting Parties therefore to double their efforts at the first meeting of the GGE now planned for November.
Lethal autonomous weapons threaten to become the third revolution in warfare. Once developed, they will permit armed conflict to be fought at a scale greater than ever, and at timescales faster than humans can comprehend. These can be weapons of terror, weapons that despots and terrorists use against innocent populations, and weapons hacked to behave in undesirable ways. We do not have long to act. Once this Pandora’s box is opened, it will be hard to close.
We therefore implore the High Contracting Parties to find a way to protect us all from these dangers.
FULL LIST OF SIGNATORIES (by country):
- Tiberio Caetano, founder & Chief Scientist at Ambiata, Australia.
- Mark Chatterton and Leo Gui, founders, MD & of Ingenious AI, Australia.
- Charles Gretton, founder of Hivery, Australia. Brad Lorge, founder & CEO of , Australia
- Brenton O’Brien, founder & CEO of Microbric, Australia.
- Samir Sinha, founder & CEO of Robonomics AI, Australia.
- Ivan Storr, founder & CEO, Blue Ocean Robotics, Australia.
- Peter Turner, founder & MD of Tribotix, Australia.
- Yoshua Bengio, founder of Element AI & Montreal Institute for Learning Algorithms, Canada.
- Ryan Gariepy, founder & CTO, Clearpath Robotics, found & CTO of OTTO Motors, Canada.
- James Chow, founder & CEO of UBTECH Rob otics, China.
- Robert Li, founder & CEO of Sankobot, China.
- Marek Rosa, founder & CEO of GoodAI, Czech Republic.
- Søren Tranberg Hansen, founder & CEO of Brainbotics, Denmark.
- Markus Järve, founder & CEO of Krakul, Estonia.
- Harri Valpola, founder & CTO of ZenRobotics, founder & CEO of Curious AI Company, Finland.
- Esben Østergaard, founder & CTO of Universal Robotics, Denmark.
- Raul Bravo, founder & CEO of DIBOTICS, France.
- Raphael Cherrier, founder & CEO of Qucit, France.
- Jerome Monceaux, founder & CEO of , founder & CCO of Aldebaran Robotics, France.
- Charles Ollion, founder & Head of Research at Heuritech, France.
- Anis Sahbani, founder & CEO of Enova Robotics, France.
- Alexandre Vallette, founder of SNIPS & Ants Open Innovation Labs, France.
- Marcus Frei, founder & CEO of NEXT.robotics, Germany
- Kirstinn Thorisson, founder & Director of Icelandic Institute for Intelligence Machines, Iceland.
- Fahad Azad, founder of Robosoft Systems, India.
- Debashis Das, Ashish Tupate, Jerwin Prabu, founders (incl. CEO ) of Bharati Robotics, India.
- Pulkit Gaur, founder & CTO of Gridbots Technologies, India.
- Pranay Kishore, founder & CEO of Phi Robotics Research, India.
- Shahid Memom, founder & CTO of Vanora Robots, India.
- Krishnan Nambiar & Shahid Memon, founders, CEO & C TO of Vanora Robotics, India.
- Achu Wilson, founder & CTO of Sastra Robotics, India.
- Neill Gernon, founder & MD of Atrovate, founder of , Ireland.
- Parsa Ghaffari, founder & CEO of Aylien, Ireland.
- Alan Holland, founder & CEO of Keelvar Systems, Ireland.
- Alessandro Prest, founder & CTO of LogoGrab, Ireland.
- Alessio Bonfietti, founder & CEO of MindIT, Italy.
- Angelo Sudano, founder & CTO of ICan Robotics, Italy.
- Shigeo Hirose, Michele Guarnieri, Paulo Debenest, & Nah Kitano, founders, CEO & Directors of HiBot
- Corporation, Japan.
- Luis Samahí García González, founder & CEO of QOLbotics, Mexico.
- Koen Hindriks & Joachim de Greeff, founders, CEO & COO at Interactive Robotics, the Netherlands.
- Maja Rudinac, founder and CEO of Robot Care Systems, the Netherlands.
- Jaap van Leeuwen, founder and CEO Blue Ocean Robotics Benelux, the Netherlands.
- Dyrkoren Erik, Martin Ludvigsen & Christine Spiten, founders, CEO, CTO & Head of Marketing at
- BlueEye Robotics, Norway.
- Sergii Kornieiev, founder & CEO of BaltRobotics, Poland.
- Igor Kuznetsov, founder & CEO of NaviRobot, Russian Federation.
- Aleksey Yuzhakov & Oleg Kivokurtsev, founders, CEO & COO of Promobot, Russian Federation.
- Junyang Woon, founder & CEO, Infinium Robotics, former Branch Head & Naval Warfare Operations Officer, Singapore.
- Jasper Horrell, founder of DeepData, South Africa.
- Toni Ferrate, founder & CEO of RO – BOTICS, Spain.
- José Manuel del Río, founder & CEO of Aisoy Robotics, Spain. Victor Martin, founder & CEO of Macco Robotics, Spain.
- Timothy Llewellynn, founder & CEO of nViso, Switzerland.
- Francesco Mondada, founder of K – Team, Switzerland.
- Jurgen Schmidhuber, Faustino Gomez, Jan Koutník, Jonathan Masci & Bas Steunebrink, founders,
- President & CEO of Nnaisense, Switzerland.
- Satish Ramachandran, founder of AROBOT, United Arab Emirates.
- Silas Adekunle, founder & CEO of Reach Robotics, UK.
- Steve Allpress, founder & CTO of FiveAI, UK.
- Joel Gibbard and Samantha Payne, founders, CEO & COO of Open Bionics, UK.
- Richard Greenhill & Rich Walker, founders & MD of Shadow Robot Company, UK.
- Nic Greenway, founder of React AI Ltd (Aiseedo), UK.
- Daniel Hulme, founder & CEO of Satalia, UK.
- Charlie Muirhead & Tabitha Goldstaub, founders & CEO of Cognitio nX, UK.
- Geoff Pegman, founder & MD of R U Robots, UK.
- Mustafa Suleyman, founder & Head of Applied AI, DeepMind, UK.
- Donald Szeto, Thomas Stone & Kenneth Chan, founders, CTO, COO & Head of Engineering of PredictionIO, UK.
- Antoine Biondeau, founder & CEO of Sentient Technologies, USA.
- Brian Gerkey, founder & CEO of Open Source Robotics, USA.
- Ryan Hickman & Soohyun Bae, founders, CEO & CTO of , USA.
- Henry Hu, founder & CEO of Cafe X Technologies, USA.
- Alfonso Íñiguez, founder & CEO of Swarm Technology, USA.
- Gary Marcus, founder & CEO of Geometric Intelligence (acquired by Uber), USA.
- Brian Mingus, founder & CTO of Latently, USA.
- Mohammad Musa, founder & CEO at Deepen AI, USA.
- Elon Musk, founder, CEO & CTO of SpaceX, co-founder & CEO of Tesla Motor, USA.
- Rosanna Myers & Dan Corkum, founders, CEO & CTO of Carbon Robotics, USA.
- Erik Nieves, founder & CEO of PlusOne Robotics, USA.
- Steve Omohundro, founder & President of Possibility Research, USA.
- Jeff Orkin, founder & CEO, Giant Otter Technologies, USA.
- Dan Reuter, found & CEO of Electric Movement, USA.
- Alberto Rizzoli & Simon Edwardsson, founders & CEO of AIPoly, USA. Dan Rubins, founder & CEO of Legal Robot, USA.
- Stuart Russell, founder & VP of Bayesian Logic Inc., USA.
- Andrew Schroeder, founder of WeRo botics, USA.
- Gabe Sibley & Alex Flint, founders, CEO & CPO of , USA.
- Martin Spencer, founder & CEO of GeckoSystems, USA.
- Peter Stone, Mark Ring & Satinder Singh, founders, President/COO, CEO & CTO of Cogitai, USA.
- Michael Stuart, founder & CEO of Lucid Holdings, USA.
- Massimiliano Versace, founder, CEO & President, Neurala Inc, USA.
Original article here.
The market for artificial intelligence (AI) technologies is flourishing. Beyond the hype and the heightened media attention, the numerous startups and the internet giants racing to acquire them, there is a significant increase in investment and adoption by enterprises. A Narrative Science survey found last year that 38% of enterprises are already using AI, growing to 62% by 2018. Forrester Research predicted a greater than 300% increase in investment in artificial intelligence in 2017 compared with 2016. IDC estimated that the AI market will grow from $8 billion in 2016 to more than $47 billion in 2020.
Coined in 1955 to describe a new computer science sub-discipline, “Artificial Intelligence” today includes a variety of technologies and tools, some time-tested, others relatively new. To help make sense of what’s hot and what’s not, Forrester just published a TechRadar report on Artificial Intelligence (for application development professionals), a detailed analysis of 13 technologies enterprises should consider adopting to support human decision-making.
Based on Forrester’s analysis, here’s my list of the 10 hottest AI technologies:
- Natural Language Generation: Producing text from computer data. Currently used in customer service, report generation, and summarizing business intelligence insights. Sample vendors: Attivio, Automated Insights, Cambridge Semantics, Digital Reasoning, Lucidworks, Narrative Science, SAS, Yseop.
- Speech Recognition: Transcribe and transform human speech into format useful for computer applications. Currently used in interactive voice response systems and mobile applications. Sample vendors: NICE, Nuance Communications, OpenText, Verint Systems.
- Virtual Agents: “The current darling of the media,” says Forrester (I believe they refer to my evolving relationships with Alexa), from simple chatbots to advanced systems that can network with humans. Currently used in customer service and support and as a smart home manager. Sample vendors: Amazon, Apple, Artificial Solutions, Assist AI, Creative Virtual, Google, IBM, IPsoft, Microsoft, Satisfi.
- Machine Learning Platforms: Providing algorithms, APIs, development and training toolkits, data, as well as computing power to design, train, and deploy models into applications, processes, and other machines. Currently used in a wide range of enterprise applications, mostly `involving prediction or classification. Sample vendors: Amazon, Fractal Analytics, Google, H2O.ai, Microsoft, SAS, Skytree.
- AI-optimized Hardware: Graphics processing units (GPU) and appliances specifically designed and architected to efficiently run AI-oriented computational jobs. Currently primarily making a difference in deep learning applications. Sample vendors: Alluviate, Cray, Google, IBM, Intel, Nvidia.
- Decision Management: Engines that insert rules and logic into AI systems and used for initial setup/training and ongoing maintenance and tuning. A mature technology, it is used in a wide variety of enterprise applications, assisting in or performing automated decision-making. Sample vendors: Advanced Systems Concepts, Informatica, Maana, Pegasystems, UiPath.
- Deep Learning Platforms: A special type of machine learning consisting of artificial neural networks with multiple abstraction layers. Currently primarily used in pattern recognition and classification applications supported by very large data sets. Sample vendors: Deep Instinct, Ersatz Labs, Fluid AI, MathWorks, Peltarion, Saffron Technology, Sentient Technologies.
- Biometrics: Enable more natural interactions between humans and machines, including but not limited to image and touch recognition, speech, and body language. Currently used primarily in market research. Sample vendors: 3VR, Affectiva, Agnitio, FaceFirst, Sensory, Synqera, Tahzoo.
- Robotic Process Automation: Using scripts and other methods to automate human action to support efficient business processes. Currently used where it’s too expensive or inefficient for humans to execute a task or a process. Sample vendors: Advanced Systems Concepts, Automation Anywhere, Blue Prism, UiPath, WorkFusion.
- Text Analytics and NLP: Natural language processing (NLP) uses and supports text analytics by facilitating the understanding of sentence structure and meaning, sentiment, and intent through statistical and machine learning methods. Currently used in fraud detection and security, a wide range of automated assistants, and applications for mining unstructured data. Sample vendors: Basis Technology, Coveo, Expert System, Indico, Knime, Lexalytics, Linguamatics, Mindbreeze, Sinequa, Stratifyd, Synapsify.
There are certainly many business benefits gained from AI technologies today, but according to a survey Forrester conducted last year, there are also obstacles to AI adoption as expressed by companies with no plans of investing in AI:
There is no defined business case 42%
Not clear what AI can be used for 39%
Don’t have the required skills 33%
Need first to invest in modernizing data mgt platform 29%
Don’t have the budget 23%
Not certain what is needed for implementing an AI system 19%
AI systems are not proven 14%
Do not have the right processes or governance 13%
AI is a lot of hype with little substance 11%
Don’t own or have access to the required data 8%
Not sure what AI means 3%
Once enterprises overcome these obstacles, Forrester concludes, they stand to gain from AI driving accelerated transformation in customer-facing applications and developing an interconnected web of enterprise intelligence.
Original article here.
Most of the attention around automation focuses on how factory robots and self-driving cars may fundamentally change our workforce, potentially eliminating millions of jobs. But AI that can handle knowledge-based, white-collar work are also becoming increasingly competent.
One Japanese insurance company, Fukoku Mutual Life Insurance, is reportedly replacing 34 human insurance claim workers with “IBM Watson Explorer,” starting by January 2017.
The AI will scan hospital records and other documents to determine insurance payouts, according to a company press release, factoring injuries, patient medical histories, and procedures administered. Automation of these research and data gathering tasks will help the remaining human workers process the final payout faster, the release says.
Fukoku Mutual will spend $1.7 million (200 million yen) to install the AI system, and $128,000 per year for maintenance, according to Japan’s The Mainichi. The company saves roughly $1.1 million per year on employee salaries by using the IBM software, meaning it hopes to see a return on the investment in less than two years.
Watson AI is expected to improve productivity by 30%, Fukoku Mutual says. The company was encouraged by its use of similar IBM technology to analyze customer’s voices during complaints. The software typically takes the customer’s words, converts them to text, and analyzes whether those words are positive or negative. Similar sentiment analysis software is also being used by a range of US companies for customer service; incidentally, a large benefit of the software is understanding when customers get frustrated with automated systems.
The Mainichi reports that three other Japanese insurance companies are testing or implementing AI systems to automate work such as finding ideal plans for customers. An Israeli insurance startup, Lemonade, has raised $60 million on the idea of “replacing brokers and paperwork with bots and machine learning,” says CEO Daniel Schreiber.
Artificial intelligence systems like IBM’s are poised to upend knowledge-based professions, like insurance and financial services, according to the Harvard Business Review, due to the fact that many jobs can be “composed of work that can be codified into standard steps and of decisions based on cleanly formatted data.” But whether that means augmenting workers’ ability to be productive, or replacing them entirely remains to be seen.
“Almost all jobs have major elements that—for the foreseeable future—won’t be possible for computers to handle,” HBR writes. “And yet, we have to admit that there are some knowledge-work jobs that will simply succumb to the rise of the robots.”
Original article here.
Robots are going to take a seat at the conference room table in 2017.
Humans are going to be more stressed than ever.
And to stay competitive with their new robot colleagues, workers are going to start taking smart drugs.
That’s according to futurist Faith Popcorn, the founder and CEO of the consultancy Faith Popcorn’s BrainReserve. Since launching in 1974, she has helped Fortune 500 companies including MasterCard, Coca-Cola, P&G and IBM.
Here are five trends you can expect to see in the workplace in 2017, according to Popcorn.
1.Coffee alone won’t keep you competitive.
Employees are going to start taking a burgeoning class of cognitive enhancers called nootropics, or “smart drugs.” These nutritional supplements don’t all have the same ingredients but they reportedly increase physical and mental stamina.
Silicon Valley has been an early adopter of the bio-hacking trend. That’s perhaps unsurprising, as techies were also the first to try the likes of food substitute Soylent. There’s an active sub-reddit page dedicated to the topic.
Nootropics will go mainstream in 2017 because “the robots are edging us out,” says Popcorn. “When you come to work you have to be enhanced, you have to be on the edge, you have to be able to work longer and harder. You have to be able to become more important to your company.”
2.Robots will rise.
Unskilled blue-collar workers will be the first to lose their jobs to automation, but robots will eventually replace white-collar workers, too, says Popcorn, pointing to an Oxford University study that found 47 percent of U.S. jobs are at risk of being replaced.
“Who would you rather have do your research? A cognitive computer or a human?” says Popcorn. “Human error is a disaster. … Robots don’t make mistakes.”
3.Everyone will start doing the hustle.
Already, more than a third of the U.S. workforce are freelancers and will generate an estimated $1 trillion in revenue, according to a survey released earlier this fall by the Freelancers Union and the freelancing platform Upwork. The percentage of freelancers will increase in 2017 and beyond, she believes. “It’s accelerating every year,” says Popcorn.
She also points to some large companies that are building offices with fewer seats than employees. Citibank built an office space in Long Island City, Queens, with 150 seats for 200 employees and no assigned desks to encourage a fluid-feeling environment.
And Popcorn points to the rise of the side hustle: People “need more money than they are being paid,” she says. And they don’t trust their employers. “People are saying, ‘I want to have two or three hooks in the water. I don’t want to devote myself to one company.'”
Younger employees in particular are not interested in working for large, legacy companies like those their parents worked for, according to research Popcorn has done. “We are really turned off on ‘big.'”
4.There will be tears.
While people have always been emotional beings, historically emotions haven’t belonged inside the office. That’s basically because workplaces have largely been run by men. But that’s changing.
“The female entry into the workplace has brought emotional intelligence into the workplace and that comes with emotion,” says Popcorn. “There is a lot of anxiety about the future, there is a lot of stress-related burnout and we are seeing more emotion being displayed in the workplace.”
That doesn’t mean you should start crying on your boss’s shoulder, though. Especially if your boss is male. While women tend to be more comfortable with their feelings, men are still uncomfortable with elevated levels of emotion, says Popcorn, admitting that these gender-based observations are generalizations.
“WE ARE SEEING MORE EMOTION BEING DISPLAYED IN THE WORKPLACE.”
-Faith Popcorn, futurist
Going forward, the futurist expects to see more stress rooms in office buildings and “more of a recognition that people are living under a crushing amount of anxiety.” A stress room would be a welcoming space for employees to go to take a break and perhaps drink kava, a relaxing, root-based tea.
Open floor plans don’t give employees any place to breathe, Popcorn points out: “It’s like being watched 24/7.” Employees put in earbuds to approximate privacy, but sitting in open spaces is not conducive to employee mental health. “It is very stressful to work in the open floors,” she says. “It’s good for real estate, you can do it with fewer square feet, but it’s not particularly good for people.”
5.The boundary between work and play will crumble.
“People are going to be working 24 hours a day,” says Popcorn. Technology has enabled global, constant communication. The WeLive spaces that WeWork launched are indicative of this trend towards work and life integration, she says. “There is no line between work and play.”
Original article here.
Outsourcing giant to axe 2,000 jobs and use ‘proprietary robotic solutions’ after clients cut spending following Brexit vote.
A British outsourcing company whose contracts include collecting the BBC licence fee is to replace staff with robots as it slashes costs.
Capita, a FTSE 100-listed firm that also runs the London congestion charge, said it needed to axe 2,000 jobs as part of a cost-cutting drive in response to poor trading.
It said it would use the money it saved from sacking thousands of staff to fund investment in automated technology across all of the company’s divisions. The announcement will fuel growing fears that human workers will have to make way for robots, as companies turn to technology to boost profits.
The Apple and Samsung supplier Foxconn was reported to have replaced 60,000 workers with robots earlier this year, while the former chief executive of McDonald’s suggested a similar tactic in response to low-paid workers’ demands for better pay and conditions.
In a gloomy statement that sent its shares to a 10-year low at one stage, Capita said it had been hit by “headwinds” as its corporate clients reined in their spending. The company unveiled plans to shore up its finances, saving £50m a year via austerity measures, including greater use of “proprietary robotic solutions” and moving around 200 jobs to India.
The chief executive, Andy Parker, said Capita, which made a pre-tax profit of £186m in the first six months of this year, would use robots to help eliminate human error and make decisions faster. The company employs 78,000 people.
“It doesn’t remove the need for an individual but it speeds up how they work, which means you need less [sic] people to do it.”
He said a human assisted by automated robotic technology could do a 40-minute job in much less time.
“They [human staff members] can then do 10 times the amount they used to, so you need less [sic] people to do the same amount of work.”
Parker said this would make the company more efficient by “taking away some of the decision-making and cutting down potential errors”.
Capita, which provides services ranging from electronic tagging for offenders to store card services for retailers, will also move some of its IT operation abroad. Parker said this would involve “a couple of hundred” jobs being shifted to India.
The company’s decisions on staffing are part of an attempt to reduce costs without causing shareholders any financial pain. Parker said the cost cuts – coupled with asset sales – would allow Capita to avoid reducing its annual dividend, which was worth £200m last year and £180m the year before.
But despite the effort to protect investors, shares in the company finished down more than 4%, having fallen more than 14% during the day, as investors were left stunned by the company’s pessimistic outlook.
Parker said he “would have thought there’d be a more positive reaction”.
Rehana Azam, the national secretary for public services at the GMB union, said: “Public services are predominantly delivered by people so it’s hard to see how they’re going to provide a cost-efficient service from call centres in another country.
“We’d want to sit down with Capita and make sure people are treated fairly in any process that ends with them losing jobs.”
Azam cast doubt on whether using robots to automate some of its systems would work. “We’ve never had a good track record with private providers delivering computerised systems. I’d like to see where there have been good examples of that kind of automation.”
Capita has struggled as its clients, which include O2, M&S, John Lewis and Dixons Carphone, have looked to cut costs in areas such as corporate travel and recruitment.
The company refused to blame the Brexit vote for the disappointing update but said earlier this year that uncertainty over the UK’s relationship with the European Union had hit its business, delaying key contracts.
Capita is predominantly UK-based, unlike bigger rivals, such as G4S and Serco, which have been sheltered to a large degree from the Brexit-related fallout by their bigger geographical footprint.
Original article here.
Artificial intelligence, machine learning, and smart things promise an intelligent future.
Today, a digital stethoscope has the ability to record and store heartbeat and respiratory sounds. Tomorrow, the stethoscope could function as an “intelligent thing” by collecting a massive amount of such data, relating the data to diagnostic and treatment information, and building an artificial intelligence (AI)-powered doctor assistance app to provide the physician with diagnostic support in real-time. AI and machine learning increasingly will be embedded into everyday things such as appliances, speakers and hospital equipment. This phenomenon is closely aligned with the emergence of conversational systems, the expansion of the IoT into a digital mesh and the trend toward digital twins.
Three themes — intelligent, digital, and mesh — form the basis for the Top 10 strategic technology trends for 2017, announced by David Cearley, vice president and Gartner Fellow, at Gartner Symposium/ITxpo 2016 in Orlando, Florida. These technologies are just beginning to break out of an emerging state and stand to have substantial disruptive potential across industries.
AI and machine learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing or application. Creating intelligent systems that learn, adapt and potentially act autonomously rather than simply execute predefined instructions is primary battleground for technology vendors through at least 2020.
Trend No. 1: AI & Advanced Machine Learning
AI and machine learning (ML), which include technologies such as deep learning, neural networks and natural-language processing, can also encompass more advanced systems that understand, learn, predict, adapt and potentially operate autonomously. Systems can learn and change future behavior, leading to the creation of more intelligent devices and programs. The combination of extensive parallel processing power, advanced algorithms and massive data sets to feed the algorithms has unleashed this new era.
In banking, you could use AI and machine-learning techniques to model current real-time transactions, as well as predictive models of transactions based on their likelihood of being fraudulent. Organizations seeking to drive digital innovation with this trend should evaluate a number of business scenarios in which AI and machine learning could drive clear and specific business value and consider experimenting with one or two high-impact scenarios..
Trend No. 2: Intelligent Apps
Intelligent apps, which include technologies like virtual personal assistants (VPAs), have the potential to transform the workplace by making everyday tasks easier (prioritizing emails) and its users more effective (highlighting important content and interactions). However, intelligent apps are not limited to new digital assistants – every existing software category from security tooling to enterprise applications such as marketing or ERP will be infused with AI enabled capabilities. Using AI, technology providers will focus on three areas — advanced analytics, AI-powered and increasingly autonomous business processes and AI-powered immersive, conversational and continuous interfaces. By 2018, Gartner expects most of the world’s largest 200 companies to exploit intelligent apps and utilize the full toolkit of big data and analytics tools to refine their offers and improve customer experience.
Trend No. 3: Intelligent Things
New intelligent things generally fall into three categories: robots, drones and autonomous vehicles. Each of these areas will evolve to impact a larger segment of the market and support a new phase of digital business but these represent only one facet of intelligent things. Existing things including IoT devices will become intelligent things delivering the power of AI enabled systems everywhere including the home, office, factory floor, and medical facility.
As intelligent things evolve and become more popular, they will shift from a stand-alone to a collaborative model in which intelligent things communicate with one another and act in concert to accomplish tasks. However, nontechnical issues such as liability and privacy, along with the complexity of creating highly specialized assistants, will slow embedded intelligence in some scenarios.
The lines between the digital and physical world continue to blur creating new opportunities for digital businesses. Look for the digital world to be an increasingly detailed reflection of the physical world and the digital world to appear as part of the physical world creating fertile ground for new business models and digitally enabled ecosystems.
Trend No. 4: Virtual & Augmented Reality
Virtual reality (VR) and augmented reality (AR) transform the way individuals interact with each other and with software systems creating an immersive environment. For example, VR can be used for training scenarios and remote experiences. AR, which enables a blending of the real and virtual worlds, means businesses can overlay graphics onto real-world objects, such as hidden wires on the image of a wall. Immersive experiences with AR and VR are reaching tipping points in terms of price and capability but will not replace other interface models. Over time AR and VR expand beyond visual immersion to include all human senses. Enterprises should look for targeted applications of VR and AR through 2020.
Trend No. 5: Digital Twin
Within three to five years, billions of things will be represented by digital twins, a dynamic software model of a physical thing or system. Using physics data on how the components of a thing operate and respond to the environment as well as data provided by sensors in the physical world, a digital twin can be used to analyze and simulate real world conditions, responds to changes, improve operations and add value. Digital twins function as proxies for the combination of skilled individuals (e.g., technicians) and traditional monitoring devices and controls (e.g., pressure gauges). Their proliferation will require a cultural change, as those who understand the maintenance of real-world things collaborate with data scientists and IT professionals. Digital twins of physical assets combined with digital representations of facilities and environments as well as people, businesses and processes will enable an increasingly detailed digital representation of the real world for simulation, analysis and control.
Trend No. 6: Blockchain
Blockchain is a type of distributed ledger in which value exchange transactions (in bitcoin or other token) are sequentially grouped into blocks. Blockchain and distributed-ledger concepts are gaining traction because they hold the promise of transforming industry operating models in industries such as music distribution, identify verification and title registry. They promise a model to add trust to untrusted environments and reduce business friction by providing transparent access to the information in the chain. While there is a great deal of interest the majority of blockchain initiatives are in alpha or beta phases and significant technology challenges exist.
The mesh refers to the dynamic connection of people, processes, things and services supporting intelligent digital ecosystems. As the mesh evolves, the user experience fundamentally changes and the supporting technology and security architectures and platforms must change as well.
Trend No. 7: Conversational Systems
Conversational systems can range from simple informal, bidirectional text or voice conversations such as an answer to “What time is it?” to more complex interactions such as collecting oral testimony from crime witnesses to generate a sketch of a suspect. Conversational systems shift from a model where people adapt to computers to one where the computer “hears” and adapts to a person’s desired outcome. Conversational systems do not use text/voice as the exclusive interface but enable people and machines to use multiple modalities (e.g., sight, sound, tactile, etc.) to communicate across the digital device mesh (e.g., sensors, appliances, IoT systems).
Trend No. 8: Mesh App and Service Architecture
The intelligent digital mesh will require changes to the architecture, technology and tools used to develop solutions. The mesh app and service architecture (MASA) is a multichannel solution architecture that leverages cloud and serverless computing, containers and microservices as well as APIs and events to deliver modular, flexible and dynamic solutions. Solutions ultimately support multiple users in multiple roles using multiple devices and communicating over multiple networks. However, MASA is a long term architectural shift that requires significant changes to development tooling and best practices.
Trend No. 9: Digital Technology Platforms
Digital technology platforms are the building blocks for a digital business and are necessary to break into digital. Every organization will have some mix of five digital technology platforms: Information systems, customer experience, analytics and intelligence, the Internet of Things and business ecosystems. In particular new platforms and services for IoT, AI and conversational systems will be a key focus through 2020. Companies should identify how industry platforms will evolve and plan ways to evolve their platforms to meet the challenges of digital business.
Trend No. 10: Adaptive Security Architecture
The evolution of the intelligent digital mesh and digital technology platforms and application architectures means that security has to become fluid and adaptive. Security in the IoT environment is particularly challenging. Security teams need to work with application, solution and enterprise architects to consider security early in the design of applications or IoT solutions. Multilayered security and use of user and entity behavior analytics will become a requirement for virtually every enterprise.
Original article here.
Elon Musk has said that there’s a “pretty good chance” that automation will entirely replace workers in the future, meaning governments will have to make up for lost wages by paying people.
The billionaire founder of Tesla and SpaceX said that rapid changes to the workforce from automation is likely to force us to introduce a “universal basic income” in which people will have to be supported by a stipend instead of working for a living.
Musk has been vocal in his warnings about the potential downside of the rise of the robots. He has invested millions in OpenAI, a project to ensure that artificial intelligence benefits mankind, rather than destroys it, and last week he said that it was only a matter of time before AI was used to take down the internet.
The idea of a universal income – an unconditional government payment – has gained traction in recent years amid growing concerns about the effect that robots will have on employment.
Customer service agents, builders and leisure industry workers are just a few jobs where opportunities may be erased or severely diminished over the coming decades, and some economists and researchers believe the majority of jobs that exist today will be done by robots in 30 years.
ABOUT | The robots are taking over… or are they?
10 professions that will almost certainly be automated…
- Loan officers
- Bank tellers
- Credit analysts
- Office clerks
- Legal secretaries
- Estate agents
…and 10 professions that probably won’t
- Social workers
- Human resources managers
- Fashion designers
- Public relations
- Computer scientists
- Health and safety engineers
Musk said this presented an opportunity rather than a threat, however. “People will have time to do other things, more complex things, more interesting things. Certainly more leisure time,” he said.
The billionaire has previously said we need to embellish our brains with artificial intelligence to avoid being left behind by robots. He has floated the idea that humans should become cyborgs if we don’t want to become the equivalent of a pet for robots, backing the idea of a “neural lace”, a new electronic layer of the brain.
Original article here.
Machine learning will drop the cost of making predictions, but raise the value of human judgement.
To really understand the impact of artificial intelligence in the modern world, it’s best to think beyond the mega-research projects like those that helped Google recognize cats in photos.
According to professor Ajay Agrawal of the University of Toronto, humanity should be pondering how the ability of cutting edge A.I. techniques like deep learning—which has boosted the ability for computers to recognize patterns in enormous loads of data—could reshape the global economy.
Making his comments at the Machine Learning and the Market for Intelligence conference this week by the Rotman School of Management at the University of Toronto, Agrawal likened the current boom of A.I. to 1995, when the Internet went mainstream. Gaining enough mainstream traction, the Internet ceased to be seen as a new technology. Instead, it was a new economy where businesses could emerge online.
However, one group of people refused to call the Internet a new economy: economists. For them, the Internet didn’t usher in a new economy per se, instead it simply altered the existing economy by introducing a new way to purchase goods like shoes or toothbrushes at a cheaper rate than brick-and-mortar stores offered.
“Economists think of technology as drops in the cost of particular things,” Agrawal said.
Likewise, the advent of calculators or rudimentary computers lowered the cost for people to perform basic arithmetic, which aided workers at the census bureau who previously slaved away for hours manually crunching data without the help of those tools.
Similarly, with the rise of digital cameras, improvements in software and hardware helped manufacturers run better internal calculations within the device that could help users capture and improve their digital photos. Researchers essentially applied calculations to the old-school field of photography, something previous generations probably never believed would be touched by math, he explained.
As people “we shifted to an arithmetic solution” to help improve digital cameras, but their cost went up as more people wanted them, as opposed to traditional film cameras that require film and chemical baths to produce good photos, he added. “Those went down,” said Agrawal, in terms of both cost and want.
Artificial Intelligence and the future | André LeBlanc | TEDxMoncton
All this takes us back to the rise of machine learning and its ability to learn from data and make predictions based on the information.
The rise of machine learning will lead to “a drop in the cost of prediction,” he said. However, this drop will result in certain other things to go up in value, he explained.
For example, a doctor that works on a patient with a hurt leg will probably have to take an x-ray of the limb and ask questions to gather information so that he or she can make a prediction on what to do next. Advanced data analytics, however, would presumably make it easier to predict the best course of remedy for the doctor, but it will be up for the doctor to follow through or not.
So while “machine intelligence is a substitute for human prediction,” it can also be “a compliment to human judgment, so the value of human judgment increases,” Agrawal said.
In some ways, Agrawal’s comments call to mind a recent research paper in which researchers developed an A.I. system that could predict 79% of the time the correct outcome of roughly 600 human rights cases by the European Court of Human Rights. The report’s authors explained that while the tool could help discover patterns in the court cases, “they do not believe AI will be able to replace human judgement,” as reported by the Verge.
The authors of that research paper don’t want A.I. powered computers to replace humans as new, futuristic cyber judges. Instead, they want the tool to help humans to make more thoughtful judgements that can ultimately improve human rights.
Original article here.
During the past few years, much has been made of the billions of sensors, cameras, and other devices being connected exponentially in the “Internet of Things” (IoT)—and the trillions of dollars in potential economic value that is expected to come of it. Yet as exciting as the IoT future may be, a lot of the industry messaging has gone right over the heads of people who today operate plants, run businesses and are responsible for implementing IoT-based solutions. Investors find themselves wondering what is real, and what is a hyped-up vision of a future that is still years away.
Over the past decade, I have met with dozens of organizations in all corners of the globe, talking with people about IoT. I’ve worked with traditional industrial companies struggling to change outmoded manufacturing processes, and I’ve worked with innovative young startups that are redefining long-held assumptions and roles. And I can tell you that the benefits of IoT are not in some far-off future scenario. They are here and now—and growing. The question is not whether companies should begin deploying IoT—the benefits of IoT are clear—but how.
So, how do the companies get started on the IoT journey? It’s usually best to begin with a small, well-defined project that improves efficiency and productivity around existing processes. I’ve seen countless organizations, large and small, enjoy early success in their IoT journey by taking one of the following “fast paths” to IoT payback:
- Connected operations. By connecting key processes and devices in their production process on a single network, iconic American motorcycle maker Harley Davidson increased productivity by 80%, reduced its build-to-order cycle from 18 months to two weeks, and grew overall profitability by 3%-4%.
- Remote operations. A dairy company in India began remotely monitoring the freezers in its 150 ice cream stores, providing alerts in case of power outages. The company began realizing a payback within a month and saw a five-fold return on its investment within 13 months.
- Predictive analytics. My employer Cisco has deployed sensors and used energy analytics software in manufacturing plants, reducing energy consumption by 15% to 20%.
- Predictive maintenance. Global mining company Rio Tinto uses sensors to monitor the condition of its vehicles, identifying maintenance needs before they become problems—and saves $2 million a day every time it avoids a breakdown.
These four well-proven scenarios are ideal candidates to get started on IoT projects. Armed with an early success, companies can then build momentum and begin to tackle more transformative IoT solutions. Here, IoT provides rich opportunities across many domains, including:
- New business opportunities and revenue streams. Connected operations combined with 3D printing, for example, are making personalization and mass customization possible in ways not imagined a few years ago.
- New business models. IoT enables equipment manufacturers to adopt service-oriented business models. By gathering data from devices installed at a customer site, manufacturers like Japanese industrial equipment maker Fanuc can offer remote monitoring, analytics and predictive maintenance services to reduce costs and improve uptime.
- New business structures. In many traditional industries, customers have typically looked to a single vendor for a complete end-to-end solution, often using closed, proprietary technologies. Today IoT, with its flexibility, cost, and time-to-market advantages, is driving a shift to an open technology model where solution providers form an ecosystem of partners. As a result, each participant provides its best-in-class capabilities to contribute to a complete IoT solution for their customers.
- New value propositions for consumers. IoT is helping companies provide new hyper-relevant customer experiences and faster, more accurate services than ever before. Just think of the ever-increasing volume of holiday gift orders placed online on “Black Monday.” IoT is speeding up the entire fulfillment process, from ordering to delivery. Connected robots and Radio Frequency Identification (RFIUD) tags in the warehouse make the picking and packing process faster and more accurate. Real-time preventive maintenance systems keep delivery vehicles up and running. Telematic sensors record temperate and humidity throughout the process. So, not only can you track your order to your doorstep, your packages are delivered on time—and they arrive in optimal condition.
So, yes, IoT is real today and is already having a tremendous impact. It is gaining traction in industrial segments, logistics, transportation, and smart cities. Other industries, such as healthcare, retail, and agriculture are following closely.
We are just beginning to understand IoT’s potential. But if you are an investor wondering where the smart money is going, one thing is certain: 10 years from now, you’ll have to look hard to find an industry that has not been transformed by IoT.
Original article here.
We may need to pay people just to live in an automated world, says space biz baron.
Elon Musk reckons the robot revolution is inevitable and it’s going to take all the jobs.
For humans to survive in an automated world, he said that governments are going to be forced to bring in a universal basic income—paying each citizen a certain amount of money so they can afford to survive. According to Musk, there aren’t likely to be any other options.
“There is a pretty good chance we end up with a universal basic income, or something like that, due to automation,” he told CNBC in an interview. “Yeah, I am not sure what else one would do. I think that is what would happen.”
The idea behind universal basic income is to replace all the different sources of welfare, which are hard to administer and come with policing costs. Instead, the government gives everyone a lump sum each month—the size of which would vary depending on political beliefs—and they can spend it however they want.
Switzerland, a country with high wages and high employment, recently held a referendum on giving its people 2,500 Swiss francs (£2,065) per month, plus 625 francs (£516) per child. It was ultimately rejected by a wide margin by the country’s fairly conservative electorate, who generally thought it would give people too much for free.
President Obama has also floated the idea in a confab with Wired: “Whether a universal income is the right model—is it gonna be accepted by a broad base of people?—that’s a debate that we’ll be having over the next 10 or 20 years.”
Robots have already replaced numerous blue collar manufacturing jobs, and are taking over more and more warehousing and logistics roles. Some—perhaps prematurely—are fretting about future AIs being developed to replace professions such as doctors and lawyers. Already, moves are being made in that direction, with chatbots which can get people off parking tickets, and an AI that can predict cases at the European Court of Human Rights. Doctors should be looking over their shoulders, too.
Musk isn’t necessarily downbeat on the automated future, however. He thinks that in the future “people will have time to do other things, more complex things, more interesting things,” and they’ll “certainly have more leisure time.” And then, he added, “we gotta figure how we integrate with a world and future with a vast AI.”
“Ultimately,” he said, “I think there has to be some improved symbiosis with digital super intelligence.”
Original article here.
For the IT sector, the concept of digital transformation represents a time for evolution, revolution and opportunity, according to Information Technology Association of Canada (ITAC) president Robert Watson.
The new president for the technology association made the statements at last week’s IDC Directions and CanadianCIO Symposium in Toronto. The tech trends event was co-hosted by ITWC and IDC with support from ITAC.
Notable sessions included the ITWC-moderated Digital Transformation panel — which featured veteran CIOs discussing the digital transformation opportunities and challenges— and IDC Canada’s Nigel Wallis outlining why Canadian business models should shift to reap IoT rewards.
Digital transformation refers to the changes associated with the application of digital technology in all aspects of human society; the overarching event theme focused on digital transformation as more than mere buzzword, but as process that tech leaders and organizations should already be adopting. Considering the IT department is the “substance of every industry,” it follows that information technology can play a key role in setting the pace for innovation and future developments, offered Watson.
Both the public and private sectors are looking to diversify operations and economies — the IT sector will be the leaders and enable development of emerging technologies including the Internet of Things (IoT): “It is coming for sure and a fantastic opportunity.”
With that in mind, here are four key takeaways from the event.
“Have you ever seen a more dynamic, exciting, and scary time in our industry?”
IDC’s senior vice president and chief analyst Frank Gens outlined reasons why IT is currently entering an “innovation stage” with the era of the Third Platform, which refers to emerging tech such as cloud technology, mobile, social and IoT.
According to IDC, the Third Platform is anticipated to grow to approximately 20 per cent by the year 2020; eighty per cent of Fortune 100 companies are expected to have digital transformation teams in place by the end of this year.
“It’s about a new foundation for enterprise services. You can connect back-end AI to this growing edge of IoT…you are really talking about collective learning and accelerated learning around the next foundation of enterprise solutions,” said Gens.
Takeaway: In a cloud- and mobile-dominated IT world, enterprises should look to quickly develop platform- and API-based services across their network, noted Gens, while also looking to grow the developer base to use those services.
“Robotics is an extremely vertical driven solution.”
Think of that classic 1927 film Metropolis, and its anthropomorphic robot Maria: While IT has come a long way from Metropolis in terms of developments in robotics, the industry isn’t quite there yet. But we’re close, noted IDC research analyst Vlad Mukherjee, and the industry should look at current advancements in the field.
According to Mukherjee, robotics are driving digital transformation processes by establishing new revenue streams and changing the way we work.
Currently, robotics tech is classified in terms of commercial service, industry and consumer. Canadian firms in total are currently spending $1.08 B on the technology, Mukherjee said.
Early adopters are looking at reducing costs; this includes the automotive and manufacturing sectors, but also fields such as healthcare, logistics, and resource extraction. In the case of commercial service robotics, the concept works and the business case is there, but not at the point where we can truly take advantage, he said.
The biggest expense for robotics is service, maintenance, and battery life, said Mukherjee.
Takeaway: Industrial robots are evolving to become more flexible, easier to setup, support more human interaction and be more autonomously mobile. Enterprises should keep abreast of robotics developments, particularly the rise of collaborative industrial robots which have a lower barrier for SME adoption. This includes considering pilot programs and use cases that explore how the technology can help improve operations and automated processes.
“China has innovated significantly in terms of business models that the West has yet to emulate.”
Analysts Bryan Ma, vice-president of client devices for IDC Asia-Pacific, and Krista Collins, research manager of mobility and consumer for IDC Canada, outlined mobility trends and why the mobility and augmented or virtual reality markets seen in the east will inevitably make their way to Canada.
China is no longer considered a land of cheap knockoffs, said Ma, adding consider the rise of companies like Xiaomi, considered “The Apple of China.”
Globally, shipments of virtual reality (VR) hardware are expected to skyrocket this year, according to IDC’s forecasts. It expects shipments to hit 9.6 million units worldwide, generating $2.3 billion mostly for the four lead manufacturers: Samsung, Sony, HTC, and Oculus.
With VR in its early days, both Ma and Collins see the most growth potential for the emerging medium coming from the consumer market. Gaming and even adult entertainment options promise to be the first use-cases for mass adoption, with applications in the hospitality, real estate, or travel sectors coming later.
“That will be bigger on the consumer side of the market,” Collins said. “That’s what we’ll see first here in Canada and in other parts of the world.”
Takeaway: Augmented reality (AR) headsets will take longer to ramp up, IDC expects. In 2016, less than half a million units will ship. That will quickly climb to 45.6 million units by 2020, chasing the almost 65 million expected shipments of VR headsets. But unlike VR, the first applications for AR will be in the business world.
“Technology is integrated with everything”
There are currently more than 3.8 billion mobile phones on the planet — just think of the opportunities, offered David Senf, vice president of infrastructure solutions for IDC Canada.
He argued that digital transformation is an even bigger consideration than security — and responding to business concerns is a top concern for IT in 2016. IT staff spent two weeks more “keeping the lights on” in 2015 versus being focused on new, innovative projects. This has to change, said Senf.
IT is living in an era of big data and advanced analytics. As cloud technology matures — from just being software-as-a-service (SaaS) to platform-as-a-service (PaaS) and infrastructure-as-a-service (IaaS) — CIOs should think about the cloud in a new way. Instead of just the cloud, it’s a vital architecture that should be supporting the business.
“Organizations are starting to define what that architecture looks like,” said Senf, adding the successful ones understand that the cloud is a competitive driver, particularly from an identity management, cost, and data residency perspective.
Takeaway: If the infrastructure isn’t already ready for big data, it might already be behind the curve. Senf notes CIOs should ensure that the IT department is able to scale quickly for change — and is ready to support the growing demands of the business side, including mobility public cloud access.
Get ready to experiment and become comfortable with data sources and analysis. This includes looking at the nature of probabilistic findings — and using PaaS, he added.
Read more: http://www.itworldcanada.com/article/the-future-of-it-four-points-on-why-digital-transformation-is-a-big-deal/383121#ixzz4MFnnfcAh
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