Category Archives: Ai

Forbes

AI And Community Development Are Two Key Reasons Why Google May Win The Cloud Wars Forbes Reflecting the rapidly increasing interest and investment in cloud computing, 10,000 developers, engineers, IT executives, and Google employees and partners gathered at Next '17, Google's annual cloud event for enterprise customers. Google showcased ... 4 ways Google Cloud will bring AI, machine learning to the enterpriseARNnet all 2 news articles »

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AI And Community Development Are Two Key Reasons Why Google May Win The Cloud Wars - Forbes

Artificial intelligence already plays a major role in human economies and societies, and it will play an even bigger role in the coming years. To ponder the future of AI is thus to acknowledge that the future is AI.

This will be partly owing to advances in deep learning, which uses multi layer neural networks that were first theorized in the 1980s. With todays greater computing power and storage, deep learning is now a practical possibility, and a deep-learning application gained worldwide attention in 2016 by beating the world champion in Go. Commercial enterprises and governments alike hope to adapt the technology to find useful patterns in Big Data of all kinds.

In 2011, IBMs Watson marked another AI watershed, by beating two previous champions in Jeopardy!, a game that combines general knowledge with lateral thinking. And yet another significant development is the emerging Internet of Things, which will continue to grow as more gadgets, home appliances, wearable devices, and publicly-sited sensors become connected and begin to broadcast messages around the clock. Big Brother wont be watching you; but a trillion little brothers might be.

Beyond these innovations, we can expect to see countless more examples of what were once called expert systems: AI applications that aid, or even replace, human professionals in various specialties. Similarly, robots will be able to perform tasks that could not be automated before. Already, robots can carry out virtually every role that humans once filled on a warehouse floor.

Given this trend, it is not surprising that some people foresee a point known as the Singularity, when AI systems will exceed human intelligence, by intelligently improving themselves. At that point, whether it is in 2030 or at the end of this century, the robots will truly have taken over, and AI will consign war, poverty, disease, and even death to the past.

To all of this, I say: Dream on. Artificial general intelligence (AGI) is still a pipe dream. Its simply too difficult to master. And while it may be achieved one of these days, it is certainly not in our foreseeable future.

But there are still major developments on the horizon, many of which will give us hope for the future. For example, AI can make reliable legal advice available to more people, and at a very low cost. And it can help us tackle currently incurable diseases and expand access to credible medical advice, without requiring additional medical specialists.

In other areas, we should be prudently pessimistic not to say dystopian about the future. AI has worrying implications for the military, individual privacy, and employment. Automated weapons already exist, and they could eventually be capable of autonomous target selection. As Big Data becomes more accessible to governments and multinational corporations, our personal information is being increasingly compromised. And as AI takes over more routine activities, many professionals will be deskilled and displaced. The nature of work itself will change, and we may need to consider providing a universal income, assuming there is still a sufficient tax base through which to fund it.

A different but equally troubling implication of AI is that it could become a substitute for one-on-one human contact. To take a trivial example, think about the annoyance of trying to reach a real person on the phone, only to be passed along from one automated menu to another. Sometimes, this is vexing simply because you cannot get the answer you need without the intervention of human intelligence. Or, it may be emotionally frustrating, because you are barred from expressing your feelings to a fellow human being, who would understand, and might even share your sentiments.

Other examples are less trivial, and I am particularly worried about computers being used as carers or companions for elderly people. To be sure, AI systems that are linked to the Internet and furnished with personalized apps could inform and entertain a lonely person, as well as monitor their vital signs and alert physicians or family members when necessary. Domestic robots could prove to be very useful for fetching food from the fridge and completing other household tasks. But whether an AI system can provide genuine care or companionship is another matter altogether.

Those who believe that this is possible assume that natural-language processing will be up to the task. But the task would include having emotionally-laden conversations about peoples personal memories. While an AI system might be able to recognize a limited range of emotions in someones vocabulary, intonation, pauses, or facial expressions, it will never be able to match an appropriate human response. It might say, Im sorry youre sad about that, or, What a lovely thing to have happened! But either phrase would be literally meaningless. A demented person could be comforted by such words, but at what cost to their human dignity?

The alternative, of course, is to keep humans in these roles. Rather than replacing humans, robots can be human aids. Today, many human-to-human jobs that involve physical and emotional caretaking are undervalued. Ideally, these jobs will gain more respect and remuneration in the future.

But perhaps that is wishful thinking. Ultimately, the future of AI our AI future is bright. But the brighter it becomes, the more shadows it will cast.

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What Will a World Governed by AI Look Like? - Futurism

Artificial intelligence is progressing rapidly. Advancements in deep learning have propelled the idea of an AI-powered world from a faraway fantasy to a fast-approaching reality. AI, whether it be in the form of personal assistants on our smartphones or data miners who predict our spending habits, is becoming more deeply integrated with our everyday lives. Whats more, were starting to see artificial intelligence make its way into larger applications.

Perhaps the most exciting applications are seen in nascent AI healthcare technologies. According to CB Insights, there are currently over 100 AI startups focused on healthcare, a sharp rise considering there were less than two dozen only a few years ago. These startups are innovating routine checkups, drug discovery and oncology research. Their technologies could assist in administering treatment to undeveloped nations and could improve existing systems in the developed world. AI and healthcare could quite possibly be a beautiful marriage, one with an enormously positive effect on society.

Here are the 4 ways AI is changing healthcare:

1. Diagnosis is becoming automated

Utilizing deep learning, the process by which machines learn and recognize complex patterns, startups are building AI systems that can more effectively analyze and diagnose illness. The Butterfly Network, a startup that secured over $100 million in funding in 2014, is working on improving ultrasound technology. Ultimately, they want their software to provide accurate diagnosis by using AI, the cloud and their 3D imaging technology.

Butterfly Network isnt the only one making strides in AI diagnosis. Another company, iCarbonX, is endeavoring to mine health data to create a big data platform that will help prevent and eliminate disease. Larger corporations are also taking an interest. IBM is backing Pathway Genomics, a company that takes small blood samples from high-risk patients in the hopes of providing early detection of cancer.

2. AI is making treatment available to more people

Microsoft is currently working on a project that aims to democratize cancer diagnosis. Their AI program analyzes cancer cells, a laborious task that previously made it an impossibility for doctors to treat a large number of cancer patients at once. Another one of their projects aims to take the guesswork out of radiological treatments, improving radiologists readings of patient data. Both technologies reduce the time doctors have to spend analyzing large amounts of data, making it possible for them to cater to more patients in less time.

3. Virtual follow-up care is alleviating the burden on nurses

Chronic pain afflicts millions. Their care requires numerous check-ups and check-ins. This requires an immense amount of work for both patients and nurses. Thankfully, companies like Sense.ly are employing artificial intelligence to lessen the hassle of outpatient treatment and care. Sense.ly has created a lifelike avatar with the ability to answer questions and assess symptoms. It also has the ability to track patient activity and adjust recommendations based on behavioral data, creating a more personalized prognosis. Systems like this reduce the hours clinicians have to work on a single case without neglecting the patients needs.

4. Its helping advance drug discovery

Big data analysis is being used to greatly reduce the time it takes researchers to find solutions to complex problems. twoXar is using predictive analysis to accelerate drug discovery like never before. And theyre not the only players. Atomwise, one of the first deep learning technologies developed to accelerate drug discovery, recently released its findings on new treatments for the Ebola virus.

Artificial intelligence in healthcare is truly amazing. It isnt limited to big business, either. Thanks to open-source projects like the python-based OpenCog, young companies have the ability to delve into the world of AI. These companies, big and small, are using AI to reshape healthcare. Their efforts to integrate AI into healthcare could greatly reduce cost and make quality, affordable healthcare available to a greater number of people.

Programmers, business leaders and healthcare providers are working to create even more powerful and precise AI systems. As they continue to revolutionize the healthcare industry, we can help shape AIs effect on our communities. Use this list as a jumping off point to get more educated about AI in healthcare and join the conversation about the rise of AI, and its effects on future doctors and patients.

Contributed by: Anthony Coggine is a HR professional turned business analyst. He hasspent more than 5 years as a recruitment consultant in a variety of industries, primarily focused on consumer technology and research.

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4 Ways AI Is Changing Healthcare - insideBIGDATA

Credit: Milles Studio/Shutterstock

Want to see better marketing results? You might want to jump on the artificial intelligence bandwagon.

A February 2017 study of 200 businesses showed that retailers plan on expanding their marketing, particularly social media and mobile marketing, and incorporating artificial intelligence to better personalize the customer's journey as well as analyze results.

The study was conducted by Sailthru, a cross-channel management platform company. When discussing what marketing channels best met marketing goals, 56 percent of businesses surveyed said their websites generate the most online revenue, with email marketing and mobile coming in next at 18 percent and 7 percent. Social media trailed at 4 percent.

Even so, email, social media and digital advertising nearly tied as the favored channels for acquiring new customers. For retention, email, followed by mobile, showed the most promise, retailers said. Thus, retailers intend to invest more in social media advertising, email automation and mobile marketing in 2017. [See Related Story: AI Comes to Work: How Artificial Intelligence Will Transform Business]

"Email is a tried-and-true digital marketing tactic. Revenue attributed directly to email varies between 30 to 50 percent for our retail clients," said Marielle Habbel, director of customer strategy and optimization for Sailthru, in a webinar discussing the results.

Habbel found it surprising that revenue generated by mobile was so low, considering how pervasive it is, and that social media, while very popular, did not show the return on investment that other channels produce. However, she said the one of the most sought-after innovations for 2017 is integrating social and mobile with email to create more powerful campaigns.

To do that, and to improve personalization of the customer's buying journey (another goal of companies), Habbel said businesses need to incorporate artificial intelligence programs.

"There's no way to bring the automation to life or bring the personalization to life without the AI," she said.

Most retailers (66 percent) already use AI in some way, with 37 percent using it for search and 33 percent using it to improve product recommendations for customers. Programmatic advertising and data analysis tied for third at 26 percent each.

Seventy-three percent of retailers felt ready for cross-channel campaigns. The rest said their companies faced roadblocks, including organizational or customer data silos that prevented smooth collaboration, and a lack of integrated technologies. In addition, more than a quarter felt their departments didn't understand how to create a cross-channel strategy to maximize resources.

Even with successful companies, one of the resource challenges for retailers is finding and retaining human talent. Habbel noted two issues: a high turnover of employees in marketing resulting in time spent training people on software, and a difficulty finding employees who are comfortable with both story and technology.

"There's a small (number) of people in the market that are able to combine those two skill sets," she said.

Marketing experts agree that "story," or content marketing that goes beyond advertising messages, is vital for successful online campaigns in email or social media.

Online marketing has shown itself successful: 81 percent of retailers met or exceeded their marketing goals in 2016, according to the survey. As companies look to the future, marketing will continue to grow, particularly for those who have already had a taste of success. Retailers will push their efforts into cross-platform integrations and personalization, particularly to incorporate artificial intelligence programs with people able to bring in the human element through content.

Karina Fabian is a full time writer and mother of four. By day, she writes reviews of business products and services for Top Ten Reviews and articles for Business News Daily. As a freelancer, she writes for Catholic educational sites and school calendars and teaches writing skills. She has 17 published novels of science fiction and fantasy. Learn more at http://fabianspace.com.

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Retailers Turn to AI to Integrate Marketing Channels - Business News Daily

Charlie Osborne | ZDNet

Neural networking could pave the way for AI systems to be given a capability which we have, until now, considered a human trait: the possession of common sense.

While some of us may have less of this than others, the idea of "common sense" -- albeit a vague concept -- is the general idea of making fair and good decisions in what is a complex environment, drawing on our own experience and an understanding of the world, rather than relying on structured information -- something which artificial intelligence has trouble with.

This kind of intuition is a human concept, but according to Facebook AI research group director Yann LeCun, leaps forward in neural networking and machine vision could one day lead to software with common sense.

Speaking to MIT's Technology Review, LeCun said there is still "progress to be made" when it comes to neural networking which is required for machine vision.

Neural networks are artificial systems which mimic the structure of the human brain, and by combining this with more advanced machine vision -- which are ways to pull data from imagery for use in tasks and decision-making -- LeCun says common sense will be the result.

For example, if you have a dominant object in an image, and enough data in object categories, machines can recognize specific objects like dogs, plants, or cars. However, some AI systems can now also recognize more abstract groupings, such as weddings, sunsets, and landscapes.

LeCun says that just five years ago, this wasn't possible, but as machines are granted vision, machine expertise is growing.

AI is still limited to the specific areas that humans train them in. You could show an AI system an image of a dog at a wedding, but unless the AI has seen one before and understands the context of the image, the response is likely to be what the executive calls "garbage." As such, they lack common sense.

Facebook wants to change this. LeCun says that while you can interact with an intelligent system through language to recognize objects, "language is a very low-bandwidth channel" -- and humans have a wealth of background knowledge which helps them interpret language, something machines do not currently have the capability to draw on in real-time to make contextual connections in a way which mimics common sense.

One way to solve this problem could be through visual learning and media such as streamed images and video.

"If you tell a machine "This is a smartphone," "This is a steamroller," "There are certain things you can move by pushing and others you cannot," perhaps the machine will learn basic knowledge about how the world works," LeCun told the publication. "Kind of like how babies learn."

"One of the things we really want to do is get machines to acquire the very large number of facts that represent the constraints of the real world just by observing it through video or other channels," the executive added. "That's what would allow them to acquire common sense, in the end."

By giving intelligent machines the power to observe the world, contextual gaps will be filled and it may be that AI could make a serious leap from programmed algorithms and set answers. One area, for example, Facebook wants to explore is the idea of AI systems being able to predict future events by showing them a few frames.

"If we can train a system to do this we think we'll have developed techniques at the root of an unsupervised learning system," LeCun says. "That is where, in my opinion, a lot of interesting things are likely to happen. The applications for this are not necessarily in vision -- it's a big part of our effort in making progress in AI."

The next 2 Facebook moves that will disrupt the world:

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Facebook AI chief: We can give machines common sense - ZDNet

For an AI to understand thirst, you must first teach it about Drake Quartz What if Messenger Day automatically decided which groups received your photos based on an AI's understanding of what thirst looks like, combined with its knowledge of who should receive thirsty posts? More ambitious still: Could AI power a bot that ...

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For an AI to understand thirst, you must first teach it about Drake - Quartz

The line for the SXSW panel Eyes in the Sky: The Future of AI and Satellites snaked around many corners in Austins JW Marriot Hotel understandably, AI coupled with space shit, bring it on.

Spaceknow Incs CEO Pavel Machalek did most of the talking during this session. Spaceknow is a San Francisco based company building an AI system that can process the petabytes of data from the hundreds of commercial satellites circling us up above.

Run an early-stage company? We're inviting 250 to exhibit at TNW Conference and pitch on stage!

We are digitizing the physical world, so we can build apps on top it, Machalek stated. According to the Czech CEO, were currently going through a sea of change in how we use satellite data.

Everything from camera technology to actual satellites to launching those satellites to space is getting cheaper. Couple that with the abundance of computer power and the development of more robust machine learning system, and it follows that we can start extracting actionable information about the world, Machalek says

His company works for lots of industrial clients, who want to know how many ships visit a certain harbor, or how many trucks pull up to a refinery to move oil. But some of the information theyre extracting is also coupled to the Bloomberg terminal, informing investors about the growth of industrial areas in China.

By counting and classifying things you get an as objective grip on reality as possible, he says, after telling a story on how the information they collect contradicted the official numbers the Chinese government put out. In a world like this, in which people make up statistics, our numbers offer an objective look.

In a similar way, Spaceknow also distributes the Africa Night Lights Index, an index that is based on the light intensity measured by satellites and then aggregated according to individual countries as a more reliable economic indicator for developing countries in Africa.

In the end, Machalek says that hed like to cover the whole world with Spaceknows system, allowing anyone with a smartphone to do real-time queries about real-world data meaning you could check from space how long the line is for the bar you want to go to, I guess.

Read next: Future voice interfaces could turn us all into geniuses -- or idiots

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Satellites and AI will bring real-time, real-world data to your phone - TNW

Forays by Google subsidiary DeepMind Health into the UKs medical institutions have been characterized by two major themes. First, amazing results powered by cutting-edge AI; and second, a lack of transparency over the handling of the UKs public-funded data. With the science going swimmingly, DeepMind Health is focusing more than ever on reassuring UK citizens that their medical records are in safe hands. Its latest plan is a public ledger that shows which bits of data its using; when; and for what purposes.

The initiative is called the Verifiable Data Audit, and was announced this week in a blogpost written by DeepMind co-founder Mustafa Suleyman and the companys head of security and transparency, Ben Laurie. The Audit technology is not yet in place, but would keep a publicly accessible record of every time DeepMind accesses hospital data, using technology related to the blockchain.

Each time theres any interaction with data, well begin to add an entry to a special digital ledger, write Suleyman and Laurie. That entry will record the fact that a particular piece of data has been used, and also the reason why for example, that blood test data was checked against the NHS national algorithm to detect possible acute kidney injury.

Like blockchain technologies, this information will be write-only it cant be edited after the fact or deleted. It will also make use of cryptographic proofs that will allow experts to verify the integrity of the data. Unlike most blockchain systems, though, the ledger wont be distributed among members of the public, but stored by a number of entities including data processors like DeepMind Health and health care providers. The company says this wont impede the verification process, and that the choice was made to make the ledger more efficient. Blockchain entities like Bitcoin are distributed among lots of different players require a lot of power (computing and literal) to compile and check as much as a small country, according to some estimates.

Speaking to The Guardian, Nicola Perrin of the Wellcome Trust said the technology should create a robust audit trail for public health data managed by DeepMind. One of the main criticisms about DeepMinds collaboration with the Royal Free [Hospital Trust] was the difficulty of distinguishing between uses of data for care and for research, said Perrin. This type of approach could help address that challenge, and suggests they are trying to respond to the concerns. DeepMind Health says it wants implement the first pieces of the audit later this year.

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Google's AI subsidiary turns to blockchain technology to track UK ... - The Verge

Flippy the robot is starting its culinary career with one simple task, but just like any rookie, it is learning on the job. With some practice and training, Flippy will be able to do everything from chopping vegetables to plating meals like a pro. Miso Robotics created the robot, which debuted in a kitchen at the restaurant chain CaliBurger in Pasadena, Calif., this week.

"Flippy will initially only focus on flipping burgers and placing them on buns," David Zito, CEO of Miso Robotics tells ZDNet. He adds, "But since Flippy is powered by our own cooking AI software, it will continuously learn from its experiences to improve and adapt over time. This means Flippy will learn to take on additional tasks including grilling chicken, bacon, onions, and buns in addition to frying, prepping, and finishing plates. Eventually, Flippy will support CaliBurger's entire menu."

The robot can be installed in kitchens in less than five minutes, and it's designed to work alongside restaurant staff. Flippy will even politely move aside if it gets in someone's way. Computer vision and deep learning software make it much smarter than your average kitchen appliance.

"Flippy features a Sensor Bar allowing it to see in 3D, thermal, and regular vision for detecting the exact temperatures of the grill as well as readiness of each burger, which will expand to other menu items as Flippy continues to learn and adapt," says Zito.

Flippy uses computer vision and AI to cook burgers. (Image: Miso Robotics)

Flippy will be installed in more than 50 CaliBurger restaurants worldwide by the end of 2019.

"The application of artificial intelligence to robotic systems that work next to our employees in CaliBurger restaurants will allow us to make food faster, safer and with fewer errors," said John Miller, chairman of Cali Group, in a statement. "Our investment in Miso Robotics is part of our broader vision for creating a unified operating system that will control all aspects of a restaurant from in-store interactive gaming entertainment to automated ordering and cooking processes, 'intelligent' food delivery and real-time detection of operating errors and pathogens."

Automation is creeping into kitchens in many forms. This week, Chowbotics (formerly Casabots) announced that it raised $5 million of Series A funding for food service robots. Then there's also Grillbot pro, which is like a Roomba for your grill. Moley Robotics is developing a fully automated and intelligent robotic chef. Various robots sell pizza, cook it, deliver it, and can even print it in outer space .

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Flippy the robot uses AI to cook burgers - ZDNet

The burdens on today's CMOs are increasing: theyre taking on larger roles and budgets while needing insight into an increasingly complex customer journey. Leah Pope, CMO, Datorama discusses how brands can leverage AI in 2017 to fuel success

As CMOs today, were operating with more responsibility than ever. Now we must simultaneously understand our customers, keep up with their every move across channels in an increasingly complex customer journey, and take on bigger budgets while adapting to a bigger seat at the executive table, as sales and service will soon roll up into our department. In many respects this has thrust marketers into becoming not only data-literate but also data-fluent practitioners.

This means we must be capable of defining the KPIs. We need to ensure that all marketing metrics, be they social, brand health, or email, align with and support our overarching business goals.

Ultimately, we are responsible for understanding how to move marketing performance and business impact in a predictable manner. Considering this is based on something that, traditionally, has been unpredictable, its a tall task. So, how do you turn a practice more akin to trial and error into a repeatable, scientific process as you attempt to tease out marketing-related insights?

If we want to make our performance predictable, it stands to reason that the insight generation process that moves the marketing needle needs to become more predictable as well.

Which brings us to a new topic that should be on every CMOs radar in 2017: How can marketers leverage emerging technology e.g., artificial intelligence (AI), more specifically, machine learning to create predictable intelligent insights that will serve as guidance to make an impact on business- and marketing-related KPIs?

In the last few years, AI and marketing-based analytic data models have made it possible to do things that marketers have talked about for decades. This conversation has converted into reality now thanks to cheap computing power, consumers that are more connected than ever, and advances in AI.

In fact, according to Gartners 2016 Priority Matrix for Digital Marketing and Advertising Hype Cycle, Predictive Analytics have a very high benefit for marketers, and an anticipated mainstream adoption of 2-5 years.

That means we can drive better marketing performance and understand ROI properly for the first time.

Today machine learning can be applied to automatically connect all of your marketing data across channels, systems and partners into a single source of truth to measure your departmental performance across all of your data. Heres the best part: They can adjust at a moments notice to take in the data from a new market, a new product launch or a new presence on Snapchat, or your latest programmatic video experiments.

Compared to the days of cumbersome, error-prone Excel sheets and constant data warehouse projects, this is a welcome paradigm shift. Its actually made the terrifying task of connecting, organizing and collecting marketing data, dare I say, easy.

So whats next for AI? Heres a pretty big hint: intelligent insights. Intelligent insights is another application of AI that works on behalf of marketers to elevate information that supports better decision making.

This introduces a new way to collaborate with your marketing technology. You provide an agenda composed of the KPIs you want to watch on an ongoing basis, and off goes your assistant into your data. Now, millions of data points get analyzed on a continual basis to tell you whats driving KPI performance, in a prioritized order of impact.

You might want to keep an eye on channel or campaign Marketing ROI, campaign engagement or conversion Rate, or campaign CPM or CTR.

Rather than rely on a labor-intensive, manual effort thats sure to miss critical findings in your ever-increasing data, imagine a marketing world where your KPI performance could be better understood via intelligent insights that help you learn whats working and what is not. That way you know exactly which campaigns are the root drivers of your marketing ROI and which campaigns are pulling it down. And, you can get granular, for example: The specific targeting method responsible for the great campaign engagement rate your team just engineered lets keep doing that. While this is merely one idea, there is a sea of opportunity for todays marketer thats provided via this technological advancement.

As a CMO always on the lookout for new ways of measuring performance and improving our marketing initiatives, I cant wait for whats next.

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2017 CMO Focus: What's Next from AI? Intelligent Insights - MarTech Advisor