Make automatic notes from your meetings : Stenos

Stenos is an iPhone app that uses speech to text technology to turn your conversations into meeting minutes. Stenos is accurate (uses state of the art AI), multi-lingual (59 supported languages) and privacy friendly (it doesn’t collect your data).

After you record a meeting, Stenos helps you perfect an summarise the minutes. You can share your notes directly with you conversation partners.

Nasscom CoE-IoT ties up with Taiwan-India AI Technology Innovation Research Center

  • Nasscom CoE-IoT has signed an intent of cooperation with Taiwan-India Artificial Intelligence Technology Innovation Research Center, Taiwan’s largest university and incubator of startups under the National Chung Cheng University.
  • Aimed at incubation support, mentorship and market access, the collaboration between Nasscom CoE IoT and Taiwan-India Artificial Intelligence Technology Innovation Research Center will help Indian tech startups to source hardware components from Taiwan during their prototyping or production phases.
  • This will also enable Taiwanese companies to set up business in India and enhance collaboration between the two nations to source hardware and electronic components leading to mutual success and greater market access.

Wipro partners with DataRobot to provide solutions in augmented intelligence

  • Bengaluru-based global IT giant Wipro has announced that it will co-develop solutions in augmented intelligence with Boston, Massachusetts-based AI solutions provider DataRobot.
  • Augmented intelligence can be defined as a design pattern that combines people and artificial intelligence working in tandem to help humans with better cognition in the areas of decision making and learning.
  • DataRobot provides an augmented intelligence platform and Wipro said that it will utilise its skills in enterprise AI and combine DataRobot’s offerings to provide clients with AI-led intelligence in businesses.

AI powered robot camera mistakes linesman’s bald head for the ball

A robot camera, trained to keep the lens trained automatically on the football using AI at a game in Inverness, Scotland, kept on mistaking the ball for the bald head on the sidelines.

The Caledonian Thistle FC doesn’t use a cameraman to film games and instead relies on an automated camera system to follow the action. Most of the smaller clubs use an automated camera; as crews and professional recording equipment can be very expensive.

CAPTCHA’s surprising relationship with AI: The story behind the squiggly letters


Most people are unaware when they confront the distorted letters and digits of CAPTCHAs in their day-to-day usage of web services that they’re being subjected to a reverse Turing test of sorts — one where the machine seeks to confirm your humanity. The Turing test, of course, is  the famous test proposed by Alan Turing to evaluate the ability of a machine to exhibit human-like behaviour. If a machine can fool a human into believing it is human, then it passes. With CAPTCHA, the human is the subject and the examiner – a machine.

It may come as a surprise to some that CAPTCHA itself is an acronym, standing for “Completely Automated Public Turing Tests to tell Computers & Humans Apart”.  What with the most useful and common implementation of it being within web services, guarding forms that seek to capture (note the homophonic similarity with CAPTCHA) user information from attacks by bots. And while that may have been the initial purpose, companies like Google have evolved CAPTCHA into even training its driverless car AI.


The term was coined by Luis von Ahn, Manuel Blum, Nicholas J. Hopper, and John Langford in 2003 in a paper titled ‘CAPTCHA: Using Hard AI Problems For Security’ which defines CAPTCHA as ‘a cryptographic protocol whose underlying hardness assumption is based on an AI problem’.

Interestingly, it posits CAPTCHA as a win-win even in the case of malicious intervention, arguing that ‘either a CAPTCHA is not broken and there is a way to differentiate humans from computers, or the CAPTCHA is broken and an AI problem is solved’.

Hence, CAPTCHAs are not simply limited to the kinds of tests being deployed currently, which rely primarily on a visual medium, to any tests wherein human success is more likely than a current computer’s. It is also for this reason that purely logical tests are rarely employed within CAPTCHAs as computers have shown themselves to be as, if not more, efficient than humans in solving them.

Characteristics of CAPTCHAs


Text-based CAPTCHAs, whose earliest implementation was by the then market leading search engine AltaVista in 1997, rely on the inability — or the unfeasibility — of current computers to do the following:

  • Invariant Recognition: The ability to recognize variations in the shapes of characters. Humans can comprehend a vast variety of variations in character shapes whereas training a computer to do the same would be a mammoth task as there are virtually limitless distortions one could effect.
  • Segmentation: The ability to separate words and characters wherein whitespaces don’t exist.
  • Parsing: The ability to separate characters based on context.

All of the above, combined with the generation of nonsensical words and phrases, is designed to defeat traditional optical character recognition along with other methods such as ‘dictionary attacks’ i.e attempts to brute force an input by using every possible combination of response possible.

Overlooked Aspects


This hasn’t prevented many (un)enterprising souls from setting up CAPTCHA solving services that pay pennies to a third-world user base for simply solving CAPTCHA tests presented to them one after the other. The clients for these services usually are blackhat online marketers looking to exploit vulnerabilities of web services for financial benefit. Unsurprisingly, these services have been compared to digital sweatshops — one more reminder of how often society seems to mimic itself in digital spaces.

Another aspect of CAPTCHAs that is often overlooked is their accessibility to those who are disabled. Though audio CAPTCHAs are now quite common, this still does not solve the issue for those with deafblindness. And what should also be concerning for many in the developing world is the lack of text-based CAPTCHAs in languages other than English. This does, however, present itself as an opportunity for startups to take on.

How you may be training Google’s Driverless Car AI with CAPTCHA


Google, having acquired popular CAPTCHA service reCAPTCHA in 2009, has implemented variations of text and image based tests across its product range, and is now using the massive human input to help train its driverless car program.

Every participation of yours in the seemingly innocuous ‘identify the car’ tests is not only keeping bots away, but helping Google build a powerful driving AI. The tests seem to cover many of the objects that one encounters on roads, from street signs, store fronts, bridges to, of course, cars. We are, it would seem, crowdsourcing the drivers of the future.

While it is an ingenious system to tap into the massive traffic that Google deals with, many have raised concerns about making users unwitting participants and some have accused the company of profiting off free labour. Many alternatives have sprung up which reward website owners for implementing their CAPTCHA system.



CAPTCHAs, clearly, are much more than meets the eye.

It is indeed pertinent and thought-provoking to ask: how do we differentiate between humans and advanced AI?

In Philip K Dick’s Do Androids Dream Of Electric Sheep?, the fictional Voigt-Kampff test is used to determine whether an individual is indeed human or an android (‘replicant’), by projecting a device at the eyes and measuring iris contraction and other biological responses to provocative questions and stories.

Considering it is inevitable that AI will graduate the CAPTCHAs of today, it may not be entirely sci-fi to imagine some version of the above making its way into our lives via integrated retina scanners and fingerprint readers in our devices, such as laptops and phones.

No matter where this goes, it is sometimes worth just taking in the rich irony of a bunch of squiggly letters standing in the way of an ever-advancing AI.

Machines are learning to argue with humans #ProjectDebater

After feats like the grand-master chess (remember Deep Blue vs. Garry Kasparov), Rubik’s Cube, Jeopardy, Space X’s space-borne supercomputer; we should have gotten used to being surprised by machines.
But then comes an attempt to equip computers with the ability to ‘truly understand language’ and then be ‘expressive’ – in other words – IBM’s  Project Debater.

Yes, a face-off has already happened between this brainy-machine and two humans in two separate debates. What stood out was Debater’s ability to listen to an opponent’s argument, undermine it, guess arguments for pre-emptive attacks and even try some humour.
Alas, areas like relevant data, human dilemma and suggestion of principled arguments also stood out as its weak spots.

Blockchain in Spain used to block corruption !

From smarter registration and tracking of transferred crypto-asset transactions to using an AI application (that researchers from the University of Valladolid have been focusing on) which generates early warning systems and traces probability of corruption; Spain is tightening its grip on corruption monsters by using technology this time.
A Spanish blockchain company that is leveraging Ethereum for fraud-reduction and a better nose on verifiability and auditability of digital transactions – is one more example of the leaps that this region is taking in embracing both blockchain and its corruption-control potential.
While the EU, via the EU Blockchain Observatory and Forum and 80 million euro worth of investments in various related projects is already on this track, Spain is following suit by tapping EU-wide blockchain and AI applications for combating corruption.

Amazon’s Foe, Walmart’s friend – Microsoft in automated checkout

What if someone could cut the queue that Amazon is leading? That too, one which is right on the edge of retail and worth billions of dollars- the automated grocery shop?
It is happening. Microsoft is pitting itself against its arch-rival in cloud business in a new game. One that Amazon started in Seattle with Amazon Go, a highly automated store wherein smartphones in the hands of customers, as well as cameras and sensors all around, allow for automated billing and payment; without the need for spending time in a check-out lane. No cashiers or registers, just subway-like gates. The technology is claimed to be so advanced that even if customers put items back on the shelf, those are automatically wiped off from their virtual baskets.
Interestingly, there were speculations that Amazon (the cloud giant) could sell the system to other retailers; and that should explain one of the triggers that sent Microsoft in this direction. Apart, of course, from the fat revenue magnet that automated check-out space can be as an aisle worth $50 billion (estimates from Loup Ventures). Potential collaboration talks with Walmart and sample technology-proofs to retailers from around the world are cementing this foray from Microsoft as a serious one.While Amazon is tight-lipped about what’s under the hood here (something about machine learning may be), Microsoft is building this around business AI (Artificial Intelligence) and partner-service layers atop Microsoft’s cloud.
The key to getting ahead of its nemesis in this lane is giving it cheap (what worked in favour of Amazon’s public cloud) to retailers, and that’s what Microsoft is, reportedly, aiming at too.

AI is entering nuclear reactors too

Soon, some North Carolina State University researchers will get busy developing control systems for nuclear power plants that lean heavily on  AI (Artificial Intelligence).
Thanks to a $3.4 million grant from the federal government (that is just one of the $23.9 million that ARPA-E, the U.S. Department of Energy’s Advanced Research Projects Administration-Energy is putting into 10 projects for finding uses in a new generation of nuclear power plants), the research consortium will explore the potential applications for the technology at nuclear power plants.
AI’s use would be in going through the mountains of data that come from a reactor, spotting patterns and alerting the unit’s human operators. Lowering maintenance and control are other goals of the new drive.

Credit Cards, Rewards and Blockchain

Getting extra points or cash-backs when one swipes cards for fuel, travel, hotels etc. is not a surprise anymore. But blockchain and AI can be soon making these rewards deeper and smarter.
Card-industry players were struggling with ways to target individual items on a store’s shelf as merchants’ inventory systems varied from company to company.
But AmEx has found respite in a blockchain technology developed by Hyperledger that allows it generation of product-targeted offers without any need for merchants to shuffle inventory management systems. Now it is on a pilot that will allow merchants to reward customers for purchasing specific items at their stores.
HSBC is not far behind, with a pilot program already rolled earlier this year for sending marketing emails to 75,000 customers using algorithms.

Singapore govt establishes AI ethics council

The Singapore government is convening a council to advise it on the ethical use of artificial intelligence (AI) and data.
Fairness, transparency and the ability to explain an AI (Artificial Intelligence)’s decision – These questions would keep a new council occupied as experts here work on ensuring alignment of AI and ethics.

A council has been convened by the Singapore government to advise it on the ethical use of AI and data.
Incidentally, government think-tank NITI Aayog in India, too, has come up with a 115-page paper titled ‘National Strategy for Artificial Intelligence’ where it discusses building capabilities to a level where India becomes AI provider for 40 per cent of the world.
AI and Ethics? Well, there is a reason Google removed ‘Do not be evil’ clause from its code of conduct a few days back.

White House and AI: Good Cop-Bad Cop-No Cop?

At the AI summit where 34 tech giants came together, technology policy man for Trump, Michael Kratsios has been, reportedly, assuring technology giants like Google, Intel, Nvidia and Apple that AI innovation would not be stifled with regulatory red-tape.

While focus on skills and research-funding, along with a pragmatic stance on regulations, would certainly be good for innovation; as rules that were meant for a different world would not be slapped mindlessly on a new era; yet, it would be imprudent to really wait to cross the bridge till it comes.
One of the many factors that will make sure AI leans towards utopia and not dystopia would be its adept regulation and direction. There is nothing like self-regulation but in addition or, worse, in absence of it, a good referee always helps.

Machine Learning: Go out-of-the-box. But not IN a Black Box

AI researchers are simply stumbling in the dark. ML is still a Black Box.
For the interpretability problem is not allowing us to see how a given AI came to its conclusions.
Ali Rahimi, an AI-researcher in California, finds company in François Chollet, a computer scientist at Google in Mountain View, as they worry about AI’s reproducibility problem wherein, thanks to inconsistencies, AI innovators still falter in learning from each other and in breaking down what’s going on under the hood.
For instance, think of ‘stochastic gradient descent’ and how after thousands of academic papers and numerous ways of applying it, we still tip toe on trial-and-error. Hell yeah, it is sexy to embrace deep-learning and all the adjacent stuff, but watch for wasted effort and suboptimal performance. Try algorithm-testing for various scenarios or ablation studies or Computer Scientist Ben Recht’s idea of shrinking it into a ‘toy problem’ may be.
Ask yourself if you are petting a Schrodinger’s cat.  It may stink.
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Duplex! You better get gargled up for…

Artificial Intelligence
Artificial Intelligence
From the good, the gothic to the gross; a whole new swathe of ways can erupt to put to use the suave, nuanced and discreet Don Draper of a Voice-Assistant that Google has just pulled out of its hat.

  1. Kids can finally hear Santa Claus sussing out how
  2. good they were all year and making Christmas-listsShrinks or Suicide-helplines can use some AI help
  3. Kidnappers can sound different too
  4. Pre-date-talks on Tinder could cut a lot of chase and ache
  5. Better Hobbes mean more Calvins. Don’t roll those eyes, we all can use an imaginary friend we reluctantly dumped in our childhoods
  6. A more-stubborn aide for Drunk Dialling fiascos
  7. Couples can have spicier verbal-brawls without breaking too much cutlery

But there’s a long way to go. Nothing’s done until Duplex can nail a woman’s ‘I am fine’ and silent grunts well. Keep at it.

Is “AI” Turning Into A Meaningless Buzzword?

Artificial Intelligence (AI) is unquestionably this year’s favorite buzzword.  Many people can’t stop gushing about it.  It’s as if anything a computer does these days is now considered AI.  And more often than not, when you pull back the curtains, it’s just marketing hyperbole.  (more…)