Category Archives: Ai

The race for artificial intelligence technology is on, and while tech giants like Google and Facebook snap up top talent to build out their own AI-powered products, a new startup has just raised a huge round of funding to help the rest of us.

Element AI a Montreal-based platform and incubator that wants to be the go-to place for any and all companies (big or small) that are building or want to include AI solutions in their businesses, but lack the talent and other resources to get started is announcing a mammoth Series A round of $102 million. It plans to use the funding for hiring talent, for business development, and also, to put some money where its mouth is, by selectively investing in some of the solutions that will be built within its doors.

Our goal remains to lower the barrier for entry for commercial applications in AI, said Jean-Franois Gagn, the CEO of Element AI, in an interview. Everyone wants to have these capabilities, its hard for most companies to pull it off because of the lack of talent or access to AI technology. That is the opportunity. The company currently has 105 employees and the plan is to ramp that up to 250 in the next couple of months, he said.

The round was led by the prolific investorData Collective, with participation from a wide range of key financial and strategic backers. They include Fidelity Investments Canada, Koreas Hanwha, Intel Capital, Microsoft Ventures, National Bank of Canada, NVIDIA, Real Ventures, and several of the worlds largest sovereign wealth funds.

This large Series A has been swift: it comes only six months after Element AI announced a seed round from Microsoft Ventures (of an undisclosed amount), and only eight months after the company launched.

Weve asked Gagn and Element AIs investors, but no one is disclosing the valuation.However, what we do know is that the startup already has several companies signed up as customers and working on paid projects; and it has hundreds of potential companies on its list for more work.

As weve been engaging with corporates and startups [to be in our incubator] we have realized that being engaged in both at the same time is not easy, Gagn said. Weve started to put together a business network, including taking positions in startups to help them by investing capital, resources, providing them with technology and bringing them all the tools they need to accelerate the development of their apps and help them connect with large corporates who are their customers. The aim is to back up to 50 startups in the field, he said.

The strategic investors also fit into different parts of Element AIs business funnel. Some like Nvidia are working as partners for business in its case, using its deep learning platform, according to Jeff Herbst, VP of business development for NVIDIA. Element AI will benefit by continuing to leverage NVIDIAs high performance GPUs and software at large scale to solve some of the worlds most challenging issues, he said in a statement. Others, likeHanwha, are coming in as customer-investors, there to take advantage of some of the smarts.

AI in its early days may have been the domain of tech companies like Google, Apple and IBM when it came to needing and commercializing it, but these days, the wide range of solutions that can be thought of as AI-based, and applications for it, can touch any and all aspects of a business, from back-office functions and customer-facing systems, through to cybersecurity and financial transactions, to manufacturing, logistics and transportation, and robotics.

But the big issue has been that up to now, the most innovative startups in these areas are getting snapped up by the large tech giants (sometimes directly from the universities where they form, sometimes a bit later).

Then consider those that are independent and arent getting acquired (yet). There still remains a gap for most companies between what skills are out on the market to be used, and what would be the most useful takeaway for their own businesses.

In other words, many considering how to use AI in their businesses are effectively starting from scratch. Longer term, that disparity between the AI haves and have-nots could prove to be disastrous for the idea of democratising intellectual power and all the spoils that come with it.

There is not a lot left in the middle, Data Collectives Matt Ocko said in an interview. The issue with corporations, governments and others trapped in that no mans land of AI have-nots is that their rivals with superior AI-powered decision making and signal processing will dominate global markets.

The idea of building an AI incubator or safe space where companies that might even sometimes compete against each other, are now sitting alongside each other talking to the same engineers to build their new products, may be an industry first.

But the basic model is not: Element AI is tackling this problem essentially by leaning on trends in outsourcing: systems integrators, business process outsourcers, and others have built multi-billion dollar businesses by providing consultancy or even fully taking the reins on projects that businesses do not consider their core competency.

The same is happening here.Element AI says that initial products that can be picked up there include predictive modeling, forecasting models for small data sets, conversational AI and natural language processing, image recognition and automatic tagging of attributes based on images, aggregation techniques based on machine learning, reinforcement learning for physics-based motion control, compression of time-series data, statistical machine learning algorithms, voice recognition, recommendation systems, fluid simulation, consumer engagement optimization and computational advertising.

I asked, and I was told multiple times, that essentially colocating their R&D next to other first, for now, is not posing a problem for the companies who are getting involved. If anything, for those who understand the big-data aspect of AI intelligence, they can see that the benefit for one will indirectly benefit the rest, and speed everything up.

That model is what made Yoshua Bengio the godfather of machine learning so excited about co-founding this company, Ocko said. That massive research advantage leads Element AI to be able to deliver technically advantaged, increasingly cost effective solutions. It means they dont have to treat AI decision making capability as a scare resource, wielded like a club on everyone else.

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Element AI, a platform for companies to build AI solutions, raises $102M - TechCrunch

Snapchat, the only social media platform left where millennials can escape their parents, has been notoriously secret about how it packed advanced augmented reality features into its mobile app.

In a research paper published June 13 on the open publishing platform Arxiv, the company seems to detail one of its tricks for compressing crucial image recognition AI while still maintaining acceptable performance. This image recognition software, if indeed used by Snap, could be responsible for tasks like recognizing users faces and other objects in the apps World Lenses.

Snaps method hinges on two techniques: simplifying the way that its convolutional neural networks (a flavor of machine learning common in image recognition) recognize shapes, and proposing a slightly different configuration of the network to offset that simplification.

With these tweaks, Snap claims to fit its algorithm into just 5.2 MBabout the size of a standard song in MP3with accuracy that just edges out Googles latest research attempt to scale down its mobile AI. With both networks taking that same 5.2 MB space, Snap scored 65.8% accuracy while Google scored 64.7% on a standard image recognition task, according to the paper. (For AI nerds, this is top-1 accuracy, or when the network is only given one shot at guessing.)

Snap isnt the first to attempt to downsize AI for mobile, but publication of the research reveals a few key points:

Weve reached out to Snap for more information, and will update if we hear back.

Snapchat has raised its AI profile in recent months by hiring a new director of engineering, Hussein Mehanna, according to a CNBC report. Mehanna had previously worked as a director of engineering in Facebooks Apple Machine Learning division.

Facebook released code for Caffe2Go, an entire framework for running AI on mobile devices in late 2016, and Google released a mobile version of the hugely-popular TensorFlow last month at its I/O developer conference. Snaps work was built using Caffe, the open-source library developed by University of California Berkeley.

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Snapchat quietly revealed how it can put AI on your phone - Quartz

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$c'R `w[Hu+b>} AqD npiov@duWwVK+!g>B5B+t0C w2<81HRP#HxBDm. v"Q`8S#Y'|Pg!MlRhJY.! m|Z0nSTC?K&O1u:'b+`)h38(Bd`l[l2O^[u~{&ht`~5JQGhZFAn4|| MQiolPALixi,.}lUKZTv@,vk]8!8+>H+d;z{snq/v~vPwG?f lj{:/)z@~ZFCQ~BCvI}t5q_2Ga]C0PvYB2p`MWD.4)Kj 1&y_V!eLk|9uH-R({ {N9qI*:I4?MGNz6t/U/'k+}!yGy{V c n}|{sxZ06$'J%eF) i@'|ZCx8igB?ZCRRo%EoVw4g ZZ%.+4[LeqKgt=Donl7F@aySI.o )[Ios}iN@%|e&H>ViV667c8|(WF+IgxAuGoQ=Jb3]m|X],[=f"JEhuSm|2D&>cpu?WFn*oZ*tkxx &P UZa9j2ACKTo6@"[Ad #`FXcEX f@u~hF9A8>=igkqF-k4=08BjN>&=']lb|Sn2LmtV=$+/dQX5e|Q$|]S1Wy=y'h#`;kg6g]Z:=r635C7>kpZM+fxvGwU}LHkwdc8mX*5^SM[)!%2P(lX3yy%w6EJ%aUb<$8jw"vgoq/ewqe2W5S|N0Mz@0D9# '`|3%"}!lLL}x]2mcH HVxqP%QKi}>Aa&}t9C1N t?,$4@mhz`>;0"5#e[ E"v;v8lEewK7hogP5jw7 rI.(3TO/ tM4s qH8Kgm-I(R/kyp{8^bu~'h/s7^dyg4EEy`3GfR[P:W, {DGn>ROgJru<5arc>3rb @]Fw^HE`xoB#k)qvE4vj@a P6`EA3&Y:HB=[=K:)4wfp-](*kK"Mqe`^ jid2/~mc]ad` DA5$}4KN"[<9`SlCv<=b16LW|H3 2#4mp@m{*"2IDf7JV=< xRzT@do@O2I3J*4NAVLW{l$QM;*}#2@R=B,[_I~(88C"%:Mw;!/C=W{oIqp+:B;PF!1'7^x9j)J 5ol7v_pOF>U'!EuzI~"$2qMq/OniE>z]Ym{29:/zNJG|Xw#@T9za%`zqW36Nl^3Xu/`e/r2 I 8zxt%z{nBDpDu2qz~4 nBr{?;Eak`y[tB{QHhA?t d+EC}]=KW)sb p"-k%^ -!`rh2P5:=Ro^}&7R+&Lh5 SQWh%xN Ng c@!GYfA>+)Te|By,,@K6:h;iOy.W[lC73| bNJe*`M~<8}[Z)|#P(GFQTV&J@!yd{Ia~7:y857o G*i]o;o l ,yl~{&9,h>wQTJGG703;PG K8#lya~otf!I0ku-n.=Q-*rl09o_IS#:SKe01v$P$$hU!r k+#Z$ 7DV#k"u7t 7)ffWhj`,cEyU'Sp$X*j1Pgy BJ3P=EjWTAnnON&E:-xV2M+(`;UAUuy1NUVc`,2NdsF[V_e~GvKI+Gk_?cqY^=u=M,1257>Xc]cOhun8;i*mG'f;;jxtgb.rvjG#?#meUn)_fFl;?{j[C`P4P9EhZmVm9gl$zh|:B6fG7FSC}/C.%mQHh{hxUQsl!sqht?:QWK*l/r.X2,9vM^]t}PQDx6=%?B;&,}-rlWGy57uru>o#_]L4bv=sKy1syqo~yKbzMtlq>s?OmxyW~Rr>}S$kC),aSydP31+E0c v;}SG &!CG?gO9xxl:du #lab?%e:,&5HaWir?TS +~o9/DquQiq'gPCi$7+QE>'X:P&Tl["#pqEVu:?*u^q|5n_jGyuv5SXp?kTR*%Dl&~J]mq/6Tw>F)Kqc1->,g +_1<{,G?!Flvg~rg.3'?rGG=Isuux.')?;^!;^N?xgf~'4;8#Xj}}`#Y'?43e]-N?_%/|yp|W|2"iw~~vq; w?SCslqz!x8},]},=Hc'u |||-fU6]75PT{hr$wG1cW!DC2nq4plX@`}u?I^6L/fY>=/tN)^)B=QnaJWd9 &DXvE"Zd(sI`[7j*]^T]Q 'Knw^TB-t K}Xz9pDZPqvD* SX"tsXsjkn|Mf$dk%D[`KdGrSW+dc4Isb0J+!c|$uI2@b7T(,RAjY:3b;:UB5l%~qm~UD;;;"FH*G1@jrzn}Th|?gfB/Q6}YC|J%w"E4t,!$zOHiQ}#?sFX qbKhggQCh>kC"<}k'$f4W;BpaJ&2yFgY 12mRnFhy{H)sd7w950 12&#r@/ d)TfNp+?JBXk@bv]41!H#R$th&6BuF_s5

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This New Atari-Playing AI Wants to Dethrone DeepMind - WIRED

US officials worry that technologies developed in Silicon Valley could be used to boost China's military capabilities.

Chinese investors looking to put money into artificial intelligence could soon face greater scrutiny.

The US government is considering limiting Chinese investment in Silicon Valley to guard technologies seen as vital to US national security, Reuters reports. The concern is that technologies developed in the US could be used to bolster China's military capabilities.

Research in AI, a term used for the ability of a machine, computer or system to exhibit humanlike intelligence, has been dominated lately by large tech companies such as Google and Facebook. The goal is to create machines that can perceive their environment and complete a wide array of every day tasks previously performed by humans.

One application of particular interest is autonomous weapons. From unmanned planes to missile defense systems to sentry robots, we've already got military hardware that functions with very little input from a human mind.

Senator John Cornyn of Texas is now drafting legislation that would give the US government far more power to block some technology investments, a Cornyn aide told Reuters.

"Artificial intelligence is one of many leading-edge technologies that China seeks and that has potential military applications," said the Cornyn aide, who declined to be identified.

Virtual reality 101: CNET tells you everything you need to know about what VR is and how it'll affect your life.

Batteries Not Included: The CNET team shares experiences that remind us why tech stuff is cool.

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US said to consider limits on Chinese investment in AI - CNET

For the last 10 years, news feeds have been the main way the mainstream user interface to discover interesting and relevant digital content.Today, news feeds, from Facebook and Twitter to LinkedIn, Instagram and Pinterest, are surfacing the interesting news and moments fromyour social network and favorite sources.

This is about to change. The push notifications on the lock screen of your personal mobile device are turning your lock screen into the new newsfeed. The lock screen is thus becoming the pivotal interface to access and experience any of the updates and content that you consider to beworth noticing.

Therefore, your lock screen and your mobile device, not the apps, become the nexus for all the personal data flows, feeding machine learningalgorithms soon running also on your personal hardware.

This is a fundamental change. It will change the way your digital experience is personalized. It will change the way AI systems can learn fromyou. And it will change the power balance between the big industry behemoths such as Facebook, Google and Apple.

Weve had push notifications bubbling under for some time now. Back in 2014, Christopher Mims of The Wall Street Journal predicted a bigsuccess to the Yo app because of the way it used the simple power of push notifications.

Yo didnt rise to the occasion, but the applications and influence of push notifications has been growing ever since. Today, the landscape for push notificationsis changing rapidly. Both Android and iOS have introduced updates on push features in a considerably fast pace.

Notifications are transforming from simple text-based boxes into adaptive elements that allow a richer and more nuanced experience, thus-calledrich notifications. Designers and developers are embracing these new possibilities, enabling a more engaging user experience. Todaysnotifications can contain text formatting, bigger images, video and updating infographics, as well as interactive features such as sharing. As a result,users are consuming more and more content directly on their lock screen.

The lock screen has become the place where your attention needs to be caught. And thus, every app is racing to invent more meaningful andengaging notifications. Nic Newman from Oxfords Reuters Institute calls this the battle for the lockscreen. In the process, applications are turning into micro-platforms that can provide notifications as branded and optimized mini-products.

The new richer interactions on your lock screen presents a new user interface paradigm and will have a major affect on personalization.

By appearing automatically on your lock screen, push notifications enable interesting things to find you, rather than the other way around. At the same time, the lock screen isnt tiedinto presenting things in a chronological order. Push notifications allow you to experience things ambiently: notifications materialize on your lockscreen automatically without your explicit action.

Importantly, you do not need to open the app to access content. Today, notifications from a news app allow you to follow thedeveloping news event directly on your lock screen. You can participate in a conversation, check photos, watch a live video and share contentwithout opening the app.

As weve seen in the news feeds of Facebook, Twitter and Pinterest, personalization algorithms are needed to curate the continuously growingflow of updates. Soon your lock screen is filtered by personalization algorithms, too.

Already, as peoples interactions are moving from the apps to the lock screen, both iOS and Android have started to automatize the waythings are presented and accessed on the lock screen. Android provides automatically triggered smart notification bundles that collect togetheruseful notifications. iPhone highlights apps based on your personal context, such as time and location. On both platforms, widgets are part ofthis development, serving richer interactions and more content without opening the app.

As an extension of you, your personal mobile device contains all your apps, thus making it a treasure trove of personal data. As an interface, the lock screenmakes it possible to combine the data of your app-specific interactions with the rich contextual data provided by your device.

Concretely, the lock screen will introduce a new algorithmic layer for personalization. The lock screen captures your social interactions andcontent consumption patterns, your favorite apps, movies, videos, music and much more. This rich data will be used to feed machine learningsystems to make personal suggestions and recommendations more relevant and contextual.

Soon your lock screen will filter push notifications actively and automatically, deciding which updates, suggestions, messages, apps, movies,recipes and ads are visible to you. With a personalized lock screen feed your device has the potential to get truly smart and personal.

When the interactions on your lock screen become richer, the data they generate becomes richer, too. Your mobile device will learn fromeverything you do more accurately than ever before.

This introduces a new opportunity to start really understanding you as a unique individual and thus go beyond the existing personalization gaps. Any individual app, even Facebook, couldnt and cant achievethis today (note: Facebook tried unsuccessfully to create their own mobile device).

Personal hardware is becoming an essential part of personalization and machine learning.

As Gary Marcus, the founder of Geometric Intelligence and NYU professor has pointed out, AI systems should be able to learn from alesser amount of data. They should be able to learnlike a child, continuously, iteratively and from everything, being able to generalize, apply and extrapolate these learnings in a useful way.

What if the missing piece for creating such a machine learning system has been a personal AI an algorithmic angel, if you will living and running on your most personal hardware, thus being able to learnwith you like a child would.

Such a personal AI running and evolving with you on your personal device is taught and fed continuously by your rich interactions andcontextual data. It evolves by iterating itself based on your feedback and personal patterns.

While learning directly from you, personal AI canutilize specialized internal and external agents that inhabit various digital environments, simultaneously utilizing the computing power in thecloud. In addition, these individual agents can process and provide domain-specific data, information and recommendations, from stock markettips to optimized travel options. The best versions of your personal AI collaborate and compete to evolve into better versions of themselves.

Everything that happens on the lock screen is captured and can be used to enhance your experience not directly by Facebook and other apps,but mainly by Google and Apple. Google Assistant and Siri will get smarter faster.

Google is already bringing machine learning into their devices using their own algorithms and hardware. Simultaneously, they are offeringdeveloper tools to optimize notifications. Apple is following suit. Samsung is trying to keep up with its recent acquisition of Viv, the next-gen AIassistant.

Will personal AI become your algorithmic angel, making sure you maintain your personal agency in tomorrows algorithmic reality? Or will it justturn your personal device into an ultimate marketing experience, thus trying to affect every decision you make?

The new age of personalized lock screen and personal AI makes the idea of algorithmic angels, your personally controlled algorithms, moretimely than ever. Ethical committees and clauses are starting, but they dont suffice. As our decision-making is augmented by intelligent machine learningsystems, we need explainable algorithms, interfaces and methods to guide and control these smart entities in an explicit and comprehensibleway.

The lock screen as a user interface provides a new interface to do so.

What if you swipe far enough left on your iPhone to see the settings and preferences of your personal AI? What if you can access variousversions of these AIs and decide which one is active for a particular moment just by swiping your lock screen? Maybe you can have amundane chat about the reasoning behind your AIs suggestions, or then you use intuitive gestures, haptics and sounds to communicate witheach other in a mutually comprehensible manner.

The ultimate conversational UI wont be an app or a bot that you need to open or call for. Its something thats present and available all thetime, engaging in a continuous dialog with you and your digital and physical environments.

The personalized lock screen creates a unique interface connecting you and your personal AI running on your most personal device. This opensup completely new opportunities for designing next-generation human-machine communication methods and interfaces that can be applied frommobile devices to AR and VR environments. Simultaneously it is the next step to augment human and machine thinking in an inseparable way.

Read more:

AI on your lock screen | TechCrunch - TechCrunch

In a very brief interview with Bloomberg, Apple CEO Tim Cook confirmed that the company has been working on an Apple car. This isnt the first time Apple talked about the companys ongoing work in the car industry.

Cook described Apples car project as the combination of three different factors self-driving cars, electric vehicles and ride-sharing. Those three things together make the car industry interesting again.

More interestingly, Cook said that Apple is more focused on self-driving technology and not necessarily the car itself. Were focusing on what we talked about were focusing on publicly is Were focusing on autonomous systems, he said.

So it looks like Project Titan is still very much a work in progress as Apple needs to figure out the technology before thinking about its marketing strategy.

This part of the interview could also confirm an earlier report that the company has been focusing on building the brain of the device instead of manufacturing fully fledged cars.

Clearly, one purpose of autonomous systems is self-driving cars there are others. And we sort of see it as the mother all AI projects, Cook told Bloomberg. Its probably one of the most difficult AI projects to work on. So autonomy is something that is incredibly exciting for us. But well see where it takes us were not really saying from a product point of view what well do. Its a core technology that we view as very important.

More recently, Apple got an autonomous vehicle test permit so that the company can start testing self-driving cars on the roads of California. So far, Apple has been using a Lexus SUV with its own sensors and devices.

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Tim Cook says Apple's car project is 'the mother of all AI projects' - TechCrunch

Automation is transforming the accounting industry in a major way. Thanks to advancements in artificial intelligence that include rapidly increasing AIs ability to process data, learn from it and draw increasingly complex conclusions, accountants are seeing a major change in their field. While robots slowly take over more and more of their tasks, accountants see increases in productivity but also a decrease in the total number of accountants needed to get the job done.

Like many industries, AI is not the death of the field but it does significantly impact the future employment opportunities available. Although accountants will still be needed, they will have to refine their skills to the higher-level thinking that AI has not yet reached, while most of their current duties will be taken on by computers.

More advanced processes are being automated

According to data by Accenture Strategy, by 2020 staff productivity in the finance industry will increase two to three times, while costs will decline 40 percent (and yes, some of this will come from staff decreasing). However, the staff theyll need will change significantly, and will include data scientists, economists and anthropologists. Meanwhile, traditional accountants will see their positions automated for faster and more accurate processing.

Forbes says that the accounting industry must adapt to a solutions based method rather than a tools based method - that is, companies are quickly moving towards a cloud-based operation to access tools more universally, so what they need to be offering customers as a selling point are the solutions to financial problems that they can come up with.

Cloud technology and third-party connections have vastly increased the amount of data artificial intelligence can access to learn from, which is what allows them to develop better automated tools.

Employees are being replaced by automation

Traditionally, the jobs under threat from automation have been viewed as primarily simple skill jobs. Things like waiting tables, checking out customers at the cash register and handling customer service have been automated with success in businesses across the country. But increasingly complex skills are getting automated thanks to artificial intelligences advancements. That means more and more of an accountants duties can be taken on by a robot.

Because most of the more tedious tasks of accounting will be performed by robots, employees left behind must focus on providing beneficial insight and guidance to customers. Accountants must adapt to prioritize advice and analysis over basic information and data processing.

Customers now have easy access to those services with literally any accountant, and may even be able to handle it themselves thanks to the widespread availability of cloud-based accounting tools. As a result, simple data processing is no longer a selling point or priority for the accounting industry.

Costs should drop across the board

With AI taking on more and more of the accountants basic duties more effectively and for cheaper and cheaper, the cost of running an accounting firm will go down. This isnt just because firms will need less accountants to handle the same volume, but because they will now have to spend much less time processing data to get to solutions and analysis to present to customers.

Customers will expect to see those savings passed along at one point - accountants will generally see the pricing in their industry fall over the next few years as services and needs change. But it doesnt necessarily mean that accountants will then struggle to make ends meet - with prices dropping, more and more small businesses can seek accounting services for their industries, which means the potential customer base can expand significantly.

Thanks to artificial intelligence, accounting will soon become less expensive, more solutions based and more widely accessible. This will enable the entire economy to get financially smarter and make access to accounting tools a norm rather than a burdensome expense.

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How AI Is Transforming Accounting - Accountingweb.com (blog)

WikiLeaks editor Julian Assange predicts an impending dystopic world where human perception is no match for Artificial Intelligence-controlled propaganda and the consequences of AI are lost on its creators, who envision a nirvana-like future.

Assange spoke of the threat of AI-controlled social media via video link at rapper and activist M.I.A.s Meltdown Festivalin the Southbank Centre, London.

READ MORE: Assange wants support for NSA whistleblower as WikiLeaks offers $10k reward to expose reporter

Speaking about the future of AI, Assange told a panel including Slovenian philosopher Slavoj iek that there will be a time when AI will be used to adjust perception.

Imagine a Daily Mail run by essentially Artificial Intelligence, what does that look like when theres only the Daily Mail worldwide? That's what Facebook and Twitter will shift into, he said.

Assange referenced the apparent intense pressure Facebook and Google were under to ensure Emmanuel Macron, and not Marine Le Pen, won last months French presidential election runoff.

When asked by M.I.A. if AI and VR technology will make society more vulnerable to becoming apolitical, Assange replied: Yes, of course we can be influenced, but I dont see that as the main problem.

"Human beings have always been influenced by sophisticated systems of production, information and experience, [such as the] BBC for example.

The technologies just amplify the power of the ability to project into the mind, he added.

The main concern in Assanges eyes centers around how AI can be used to advance propaganda.

The most important development as far as the fate of human beings are concerned is that we are getting close to the threshold where the traditional propaganda function that is employed by BBC, The Daily Mail, and cultures also, can be encapsulated by AI processes, Assange said.

When you have AI programs harvesting all the search queries and YouTube videos someone uploads it starts to lay out perceptual influence campaigns, twenty to thirty moves ahead. This starts to become totally beneath the level of human perception.

Read more

Using Google as an example, and comparing the wit involved to a game of chess, he said at this level human beings become powerless as they cant even see it happening.

Admitting his vision was dystopian, he suggested that he could be wrong.

Maybe there will be a new band of technologically empowered human beings that can see this [rueful] fate coming towards us, [which] will be able to extract value or diminish it by directly engaging with it that's also possible.

Another insight offered by the WikiLeaks founder was his opinion that engineers involved in AI lack perception about what theyre doing.

I know from our sources deep inside the Silicon Valley institution[s] that they genuinely believe that they are going to produce AI that's so powerful, relatively soon, that people will have their brains digitized, uploaded to these AIs and live forever in simulation, therefore have eternal life.

It's like a religion for atheists, he added. And given youre in a simulation, why not program the simulation to have endless drug and sex orgy parties around you.

Assange said this vision makes them work harder and the dystopian consequences of their work is overshadowed by cultural and industrial bias to not perceiving it.

He concluded that the normal perception someone would have regarding their work has been supplanted with this ridiculous quasi-religious model that's it all going to lead to nirvana.

Read the rest here:

Future of humanity under threat from AI-controlled propaganda Assange (VIDEO) - RT

In 1950, Alan Turing, already famous for helping to crack the German Enigma code during World War II, devised the Turing test to define intelligence in machines. Could a computer, Turing asked, fool a human into thinking he was interacting with another person, or imitate human responses so well that it would be impossible for a person to tell the difference? If the machine could, Turing proposed, it could be considered intelligent. Turings thought experiment spawned scores of science-fiction tales, such as the 2015 hit movie Ex Machina. Now, artificial intelligence (AI) and autonomous algorithms are not only passing the Turing test every day but, more importantly, are making and saving money for the businesses that deploy them.

CenturyLink is one of the largest telecommunications providers in the United States, serving both small and large businesses nationwide. The company collects thousands of sales leads from the businesses it serves, and it wishes to interact with them in the intimate, personal manner consumers have come to expect. Pursuing those leads more effectively would accelerate the companys growth, and converting and upselling a larger percentage of hot leads (people who have expressed interest in the companys services by filling out a form, clicking on an ad, or emailing the company) would boost the companys bottom line.

Accordingly, in the latter half of 2016, CenturyLink made a small investment in an AI-powered sales assistant made by Conversica to see if it could help the company identify hot leads without hiring an expensive army of sales reps to comb through the leads. The Conversica AI, a virtual assistant named Angie, sends about 30,000 emails a month and interprets the responses to determine who is a hot lead. She sets the appointment for the appropriate salesperson and seamlessly hands off the conversation to the human.

The potential customer gets a prompt and helpful outreach from Angie, and the reps who may each have 300 accounts save time because Angie vets the inquiries to identify the ones with the most potential. The reps also become more efficient because Angie routes the right leads to the right reps. In the small pilot CenturyLink ran, Angie could understand 99% of the emails she received; the 1% that she couldnt understand were sent to her manager.

According to Scott Berns, CenturyLinks Director of Marketing Operations, the company has approximately 1,600 sales people, and the Angie pilot started with four of them. That number soon rose to 20, and continues to grow today. Initially, Angie was identifying about 25 hot leads per week. That has now increased to 40, and the results have certainly validated the companys investment. It has earned $20 in new contracts for every dollar it spent on the system.

Tom Wentworth, Chief Marketing Officer at RapidMiner, a company that provides an analytical tool for data scientists, had a problem that was similar to CenturyLinks. Like many software companies, RapidMiner offers free trials, and Wentworth was struggling to serve the approximately 60,000 users who come to the companys site each month for the free trial. Many of the visitors using RapidMiners software, and needing help, are not paying anything for the service. So, how could Wentworth help them in a cost-effective way?

The company had a popular chat feature on its site, but its salesforce was overwhelmed and spending a great deal of time sorting through the chat sessions to find potential customers. It was like looking for the proverbial needle in a haystack.

Wentworth approached a friend who suggested he try a chat tool called Drift, which would ask a visitor initiating a chat, What brought you to RapidMiner today? The visitor would respond, and the Drift bot would provide one of seven potential follow-up answers. For example, a visitor might say, I need help, and Drift would send him or her to the support section of the website.

Drift was relatively easy to set up. Wentworth, like CenturyLink, started small, running the tool on a few of RapidMiners smaller web pages to test how helpful it was.

In less than two weeks, he had deployed it on every page.

The Drift bot now conducts about a thousand chats per month. It resolves about two-thirds of customer inquiries; those that it cannot, it routes to humans. In addition to Wentworth, who is monitoring the tools interactions, two co-op college students support the inquiries part-time. Wentworth told me that Drift is generating qualified leads for the sales team by making customers. Its the most productive thing Im doing in marketing, he said.

Every day, Wentworth reviews conversations people have had with Drift. Ive learned things about my visitors that no other analytics system would show, said Wentworth. Weve learned about new use cases, and weve learned about product problems.

This is the strength of an AI agent that can elicit information like a person, rather than an analytics tool that simply finds patterns in the data it collects, like a machine.

In 2016, Epson America, the printer and imaging giant, piloted the same Conversica AI assistant as CenturyLink. Chris Nickel, Epsons senior manager of commercial marketing, was drowning in all the leads he was getting for the companys diverse line of products: big printers, projectors, scanners, point of sale solutions, and industrial robots. Epson America was getting 40,000 to 60,000 leads per year from trade shows, direct mail, email marketing, social media, print and online advertising, and a successful brand awareness campaign. The leads would pour in, and whether they were good, bad, qualified or not, they would all be turned over to salespeople whose availability to follow up was inconsistent.

After implementing the AI assistant, Epsons leads are now followed up promptly and persistently until their AI assistant gets a response. Because the outreach to leads takes 6-8 times, Conversica is a true force multiplier for our sales team, say Nickel. After a lead is passed to one of Epsons partners, the AI assistant follows up to make sure the customer was satisfied. Sometimes, the response to that follow-up identifies a new sales opportunity, such as everything went great, and actually we are looking to buy another 60 projectors, giving Epson the opportunity to quickly capitalize on a new sales opportunity before the competition. Or it can uncover an unresolved customer support issue, such as Im having a problem with my projector.

As Nickel told me, Before, if we gave 100 leads to the reps, we might get a couple of responses from customers. Now, if we give 100 leads to the AI assistant, we get 50 responses. Epson reports that the official response rate with the AI assistant is 51%, representing a 240% increase from the baseline established at the beginning of the pilot, and a 75% increase in qualified leads. According to Nickel, that has produced $2 million in incremental revenue in just 90 days.

Because the AI tools that Epson America, RapidMiner, and CenturyLink deployed are offered as-a-service, it was easy for these companies to conduct pilots, and then scale up. Clearly, its worthwhile for companies to test AI-powered chat or email tools to see if they can convert more leads, and improve their understanding of what customers want and need.

When it comes to AI in business, a machine doesnt have to fool people; it doesnt have to pass the Turing test; it just needs to help them and thereby help the businesses that deploy them. And that test has already been passed. As one CMO told me, AI tools are the only way I can scale helpfulness to a global community of 200,000-plus users with a team of two.

View post:

How AI Is Streamlining Marketing and Sales - Harvard Business Review

Over the past three months, Nvidia's (NASDAQ:NVDA) stock has been upgraded by several financial services firms including Goldman Sachs (NYSE:GS), Citigroup (NYSE:C), and Bernstein, while some others have downgraded the stock, such as Pacific Crest. In an article published in December, last year, I said Nvidia's stock could scale new highs if the company's revenue continues to grow at a CAGR of 20% plus in the foreseeable future. At that time, the stock created a new high around $120, before correcting almost 20% afterwards.

I also cautioned investors that the stock could go through spine-chilling volatility, and that's exactly what is happening now. The commentaries of several sell-side analyst firms fueled the extent of volatility beyond what happens under normal circumstances. My medium-term target for the stock is $200+, albeit with continued volatility. The new catalyst for the stock will be the availability of its HGX-1 platform at the hyperscale space.

Nvidia: Revisiting the Bull Thesis

My investment thesis was based on the expectation that Nvidia's revenue will grow at a CAGR of 20% plus in the next three years. The primary revenue growth driver will be the expanding application of artificial intelligence (AI) and/or deep learning (DL) across various industries. Let's focus on Nvidia's competitive advantage in AI/DL.

Nvidia's DGX-1 platform is its trump card to lead the next generation of AI-wave leveraging the TensorFlow software library, originally developed by Google (NASDAQ:GOOGL)(NASDAQ:GOOG). Nvidia recently launched a partner program with hyperscale vendors, such as Foxconn, Inventec, Quanta and Wistron, for its HGX-1 AI reference platform. What's the difference between DGX-1 and HGX-1? Well, HGX-1 is the hyperscale version of the DGX-1 platform. The launch of the partnership program will have a strong and sustainable impact in the HPC (high performance computing) space via hyperscale players.

Investors need to understand how the advantages of TensorFlow coupled with Nvidia's HGX-1 reference architecture will boost its revenue in the foreseeable future, which Nvidia's stock at today's price around $150 hasn't factored in.

CUDA, HGX and TensorFlow

TensorFlow has become extremely popular since its inception in late 2015 by the Google Brain Team. Its appeal lies in its usage of data flow graphs for solving complex mathematical problems related to building efficient neural networks. Add to that its support for multiple GPUs and CPUs via a single API. This is the secret sauce behind the immense success of TensorFlow, out-competing other AI-related software libraries, such as torch, caffe and theano in terms of speeding up the training process of the neural networks.

Engineers at Nvidia were quick to understand TensorFlow's competitive advantage over other software libraries. While Intel (NASDAQ:INTC) was busy to make its MKL (math kernel library) more versatile via incorporating the Neon deep learning framework of Nervana, the startup which Intel acquired almost a year ago, Nvidia silently made its CUDA parallel computing software platform compatible with TensorFlow.

The DGX-1 platform, which is basically a parallel processing-based hardware accelerator with eight Nvidia Tesla P100 GPUs, is the platform that gave birth to HGX-1. Both DGX-1 and HGX-1 connect the eight Tesla P100 GPUs via NVLink interconnect. With the introduction of HGX-1 earlier this year and then making it available to end-users via different hyperscale vendors, Nvidia has opened the door for running different kinds of AI/DL workloads for various industries.

How HGX-1 would expand the scope of DGX-1 via taking the latter to the hyperscale space? Okay, before addressing the issue let's delve a bit deeper into how Nvidia's upcoming Tesla V100, i.e., Tesla powered by Volta GPU architecture, will help DGX-1 deliver much faster performance compared to other GPU-based systems. The Volta architecture will be made to support Tensor-based AI/DL operations, which implies the HGX-1 will also deliver Tensor-based performance boost at the hyperscale space.

HGX At Hyperscale: What Does It Really Mean?

What does HGX at the hyperscale space mean for investors? Simple. It means more revenue for Nvidia. Since hyperscale computing enables datacenters to deploy distributed computing environments across the globe via scaling only a few servers to lots of servers, Nvidia's GPUs will see a steady rise in adoption. However, that doesn't necessarily mean all the datacenters across the world will need to deploy the high end Tesla P100 or the upcoming Tesla V100 GPUs.

Only the hyperscale datacenters will need them. For the traditional datacenters, Nvidia's Pascal-powered midrange Quadro workstation GPUs will be enough. This essentially means HGX has the ability to boost the overall demand for Nvidia's server-grade GPUs. Nvidia's decision to launch the HGX partner program will help it grab a significant portion of the AI/DL market share from archrivals Intel and AMD (NASDAQ:AMD).

Intel is also trying to make MKL compatible with TensorFlow. However, the process isn't complete yet. I believe Intel has potential to compete with Nvidia in the parallel processing space. But due to its FPGA-dominated business model and late entrance in the AI/DL marketplace, it won't be able to become a real competitor of Nvidia just yet.

Unfortunately for Nvidia, though, AMD has made significant progress in the last six months. AMD, with its upcoming Radeon Instinct line of GPUs along with its upcoming Zen-based Naples CPUs (bundled with the SenseMI technology), could be Nvidia's real competitor, but for that to happen the OpenCL (open computing language) software library (which is the CUDA equivalent for AMD, and to some extent Intel) needs to support TensorFlow. Please refer to my article mentioned at the beginning to learn more about CUDA and OpenCL.

Valuation

Nvidia's trailing 12-month revenue is $7.5 billion. A CAGR growth rate of 20%, which is quite possible due its AI/DL leadership as analyzed above, will catapult its revenue closer to $13 billion in 2020. And since such an incredible growth is almost given, I won't be surprised if the Street offers a P/S multiple of 17/18x to its stock in the next six months. After a year, Nvidia's revenue will be around $9 billion at the CAGR rate mentioned above, and at ~15x P/S multiple the stock will get closer to or even slightly beyond the $200 level. So it's a strong possibility that the stock will cross the $200 mark in the next six to twelve months.

NVDA Revenue (TTM) data by YCharts

Final Words

Nvidia is a secular bull story. However, you need nerves of steel to be a part of the story. AI/DL was a concept even a few years ago, and has started to take the shape of an industry just now. I would recommend risk-tolerant investors to hold the stock as a long-term investment.

Disclosure: I am/we are long NVDA, GOOGL.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Link:

Nvidia's Next Big Thing: The HGX-1 AI Platform - Seeking Alpha