How Effective are top Education Apps?

 Good feedback as to what works in the new contexts.

Top Educational Apps for Children Might Not Be as Beneficial as Promised

Penn State News, Katie Bohn, May 11, 2021

An analysis of the most frequently downloaded educational apps for kids by a team of researchers led by the Pennsylvania State University Brandywine found such apps may not provide high-quality educational experiences. The researchers used previous research on the pillars of learning to develop criteria for the assessment of the top 100 children's educational apps from the Google Play and Apple apps stores, among others. After the apps were scored from 0 (low) to 3 (high) for each pillar of learning, the researchers found a score of 1 was most common for each app with regard to all four pillars. The University of Michigan’s Marisa Meyer said, “If app designers intend to engender and advertise educational gains through use of their apps, we recommend collaborating with child development experts in order to develop apps rooted in the ways children learn most effectively. .... '

Automatically Generating Reinforcement Learning Algorithms

Can be expected that many current machine learning techniques will move towards automation.  Papers mentioned are worth looking at.

DeepMind’s AI automatically generates reinforcement learning algorithms
Kyle Wiggers in VentureBeat

 In a study  published on the preprint server Arxiv.org, DeepMind researchers describe a reinforcement learning  algorithm-generating technique that discovers what to predict and how to learn it by interacting with environments. They claim the generated algorithms perform well on a range of challenging Atari video games, achieving “non-trivial” performance indicative of the technique’s generalizability.

Reinforcement learning algorithms — algorithms that enable software agents to learn in environments by trial and error using feedback — update an agent’s parameters according to one of several rules. These rules are usually discovered through years of research, and automating their discovery from data could lead to more efficient algorithms, or algorithms better adapted to specific environments.  ... " 

Feedback loops for Neural Nets

I remember something similar posed in the 90s, tat feedback could converge to better results. Or at least produce some better next step position.   Don't recall any work suggest progress back then.  Now its here?  Lots more detail at the link.

For Better Deep Neural Network Vision, just add Feedback (loops)  in MIT News
The DiCarlo lab finds that a recurrent architecture helps both artificial intelligence and our brains to better identify objects.

Sabbi Lall | McGovern Institute for Brain Research 

Your ability to recognize objects is remarkable. If you see a cup under unusual lighting or from unexpected directions, there’s a good chance that your brain will still compute that it is a cup. Such precise object recognition is one holy grail for artificial intelligence developers, such as those improving self-driving car navigation.

While modeling primate object recognition in the visual cortex has revolutionized artificial visual recognition systems, current deep learning systems are simplified, and fail to recognize some objects that are child’s play for primates such as humans.

In findings published in Nature Neuroscience, McGovern Institute investigator James DiCarlo and colleagues have found evidence that feedback improves recognition of hard-to-recognize objects in the primate brain, and that adding feedback circuitry also improves the performance of artificial neural network systems used for vision applications. ... " 

More on Dicarlo Lab at MIT, with more on the above and related activity

Cybernetics and the Human Use of Human Beings

Cybernetics is not a much used term these days,  probably its closest term today is 'Computer Science',  but that implies a colder, technical aspect than we are dealing with today, when we introduce cognitive methods as sensors.   I note that they mention the dangers of its use by 'totalitarianism',  which still has an extreme ring that most people reject.    But remember too that Cybernetics is a Russian term, and ultimately links to the Soviet and German socialist experiments,  which have clearly failed.   Wiener though was prescient, and his work is worth reading even today.

What Would the Father of Cybernetics Think About A.I. Today?
Looking back on Norbert Wiener’s seminal 1950 book, The Human Use of Human Beings.  By  Seth Lloyd in Slate. 

The Human Use of Human Beings, Norbert Wiener’s 1950 popularization of his highly influential book Cybernetics: or Control and Communication in the Animal and the Machine (1948), investigates the interplay between human beings and machines in a world in which machines are becoming ever more computationally capable and powerful. It is a remarkably prescient book, and remarkably wrong. Written at the height of the Cold War, it contains a chilling reminder of the dangers of totalitarian organizations and societies, and of the danger to democracy when it tries to combat totalitarianism with totalitarianism’s own weapons.

Wiener’s Cybernetics looked in close scientific detail at the process of control via feedback. (Cybernetics, from the ancient Greek for helmsman, is the etymological basis of our word governor, which is what James Watt called his pathbreaking feedback control device that transformed the use of steam engines.) Because he was immersed in problems of control, Wiener saw the world as a set of complex, interlocking feedback loops, in which sensors, signals, and actuators such as engines interact via an intricate exchange of signals and information. The engineering applications of Cybernetics were tremendously influential and effective, giving rise to rockets, robots, automated assembly lines, and a host of precision-engineering techniques—in other words, to the basis of contemporary industrial society. .... "

Feedback and Blacker Boxes

Thoughts on the topic of complexity and understanding the operational specifics of what we have done.

The Blacker the Box  By Michael Kaminsky

There has been a lot of discussion in the data science community about the use of black-box models, and there is lots of really fascinating ongoing research into methods, algorithms, and tools to help data scientists better introspect their models. While those discussions and that research are important, in this post I discuss the macro-framework I use for evaluating how black the box can be for a prediction product.

In this post I do not get into the weeds of complexity penalization algorithms or even how to weigh the tech debt associated with additional complexity. Instead, I want to take a step back and discuss how I think about “prediction” problems at a more macro level, and how I value accuracy and complexity for different types of problems.

The thesis of this post is:

The faster the feedback on prediction accuracy, the blacker the box can be. The slower the feedback, the more your models should be explicit and formal.

In this post I talk through some examples of fast feedback problems and what makes them more amenable to black-box prediction algorithms (provided you have the proper infrastructure) as well as slower feedback problems and how one might approach predictions in those situations.

Fast Feedback

The machine learning community spends the bulk of its time working on and talking about fast feedback problems. Problems with fast feedback are defined by 1) the ability to quickly evaluate the correctness of a prediction1 and 2) the ability to play the game near infinite amounts of time2. Some examples of fast feedback problems are:

Chess: it is easy to verify which player has won or lost. Feedback takes only as long as the length of the game.
Conversion for an Ad Placement: Feedback to Google or Facebook on whether you clicked a given advertisement, and whether you subsequently converted  3 is nearly instantaneous.
Movie Recommendations: For a given list of potential movies to watch, Netflix gets near instantaneous feedback when you do or do not watch some of the content they have elevated for you. .... "

Its All About Continuous Learning

Our own early experiments in AI failed because we ended up needing expensive continuous Maintenance.   We need continual learning, and we need to plan for that up front.  I always recommend that for projects that seek to integrate intelligence in process.   Feedback will likely be sparse at first,  but needs to be built-in and well designed.

Good piece in O'Reilly:

Why continuous learning is key to AI
A look ahead at the tools and methods for learning from sparse feedback.   By Ben Lorica August 7, 2017

" ... I take for granted that future AI systems will rely on continuous learning as opposed to algorithms that are trained offline. Humans learn this way, and AI systems will increasingly have the capacity to do the same. Imagine visiting an office for the first time and tripping over an obstacle. The very next time you visit that scene—perhaps just a few minutes later—you’ll most likely know to look out for the object that tripped you. .... " 

Closing the Loop

From the Edge Foundation.  A Conversation with Chris Anderson.  I have worked with process control systems that are closed loop, and designed to be ...  We have many in our lives,  but many are hidden, from the lowly thermostat to ambient computers that continually wait for our commands.  In some cases its very obvious when the loop is closed,  but in most computing systems it is not. You should be able to tell if you map the process.

In the Edge: 
Closing the loop is a phrase used in robotics. Open-loop systems are when you take an action and you can't measure the results—there's no feedback. Closed-loop systems are when you take an action, you measure the results, and you change your action accordingly. Systems with closed loops have feedback loops; they self-adjust and quickly stabilize in optimal conditions. Systems with open loops overshoot; they miss it entirely.

Chris Anderson is the CEO of 3D Robotics and founder of DIY Drones. He is the former editor-in-chief of Wired magazine.  ..... "     Podcast and text ... "

Amazon Getting Fast Feedback

In the Verge:  I like the idea of a company getting frequent feedback from its employees.   Providing you can do something with the results.  Gathering trends, ideas, watch-outs ...    Too often these things are done yearly.  Too infrequent.  Need to attach analytics to this stream,  and link what is found to the people who can so something with it.   Really also an ideal cognitive application to processes that get work done.

Feeling Virtual Reality

In TechDirt: An area we examined to communicate feelings like 'softness' to consumers.    This is a Kickstarter thing, don't know how well it works, but worth an examination.

" ... True virtual reality — the kind we've been envisioning now for decades — is inching ever closer to, well, reality. But while most of the focus is new devices that let you see a virtual world, there are some people out there working on the other senses to round out the simulated experience. This week, we're looking at Gloveone, a haptic feedback system that wants to do for touch what devices like the Oculus Rift are doing for sight. ... " 

Kroger and Omnichannel Balance

Feedback in general is always a key interest, it can exist at many levels and sources.  It still remains difficult thing to combine different kinds and levels of feedback.  This is becoming more interesting as social data is integrated into feedback results ...

How Kroger strives for the omnichannel balance 
Customer feedback is key in shaping a retailer's transition from traditional to omnichannel, said Shashank Saxena, Kroger's director of digital and e-commerce technology. He also advises retailers to keep up with big-picture trends, tweak business models as trends change and take great care when testing changes to core brands. ....   "

Crowdsourcing for Better Employee Feedback

Pretty simple idea.   " ... A new study links job satisfaction with review satisfaction. Use these 5 crowdsourcing techniques to improve your employee reviews--and your workers' happiness with their jobs. ... " 

P&G's Changes in Spending

In AdAge:   A good detailed piece on P&G's moves in ad spending. " ... P&G's marketing spend is about one-third digital, CEO says  Procter & Gamble is directing as much as 35% of its marketing budget to digital media as the company tries to match customer presence online and on mobile devices, CEO A.G. Lafley said. Digital has been a faster way to reach customers and get their feedback, other executives added. P&G brands with a large digital concentration include Pampers, Secret and Old Spice. ... " 

Brainwaves Added to the Quantified Self

Word of a kickstarter project called Melon that would gather brainwaves.  Another example of the quantified self. Also, related this to neuromarketing, there might be the potential to market you brainwaves under different contexts.  " ... The device will use EEG (electroencephalography) to measure brain activity and will come with an iOS app that will provide feedback to the user on “how focused” they are during given any point. According to the screenshots, users will be able to log what activity their doing for a given time and the Melon headband will provide a “focus score” on a 1 – 10 scale to inform users when their brain most focused. Melon’s iOS app will also contain a number of games and exercises to help users improve their focus while using their band. ... " 

Shoppers Want Mobile Empowerment

On the Need for Mobile: " ... While American and European shoppers show little interest in purchasing groceries through mobile devices, a survey by Symphony EYC shows that solid majorities want to be able to use mobile devices for in-store price comparison. Additionally, 72% of Americans and 65% of Europeans say they want mobile services that allow them to share ideas on products and offer feedback ... " .   The ability to provide feedback is interesting .... but very high.  People want the ability, but using the one percent rule ... only a very few would use it.  And what does purchasing mean?  Typical grocery products, or a much broader selection?

Techniques in Sentiment Analysis

In CACM:   Excellent overview piece on the subject.  The abstract itself has interest: " ... Sentiment analysis (or opinion mining) is defined as the task of finding the opinions of authors about specific entities. The decision-making process of people is affected by the opinions formed by thought leaders and ordinary people. When a person wants to buy a product online he or she will typically start by searching for reviews and opinions written by other people on the various offerings. Sentiment analysis is one of the hottest research areas in computer science. Over 7,000 articles have been written on the topic. 

    Hundreds of startups are developing sentiment analysis solutions and major statistical packages such as SAS and SPSS include dedicated sentiment analysis modules. There is a huge explosion today of 'sentiments' available from social media including Twitter, Facebook, message boards, blogs, and user forums. These snippets of text are a gold mine for companies and individuals that want to monitor their reputation and get timely feedback about their products and actions. Sentiment analysis offers these organizations the ability to monitor the different social media sites in real time and act accordingly. Marketing managers, PR firms, campaign managers, politicians, and even equity investors and online shoppers are the direct beneficiaries of sentiment analysis technology .... " 

Cheesecake Factory Restaurant Analytics

The Cheesecake Factory delivers an exceptional brand experience with IBM Big Data analytics http://goo.gl/Mfn5c #IBMPWLC

I had yet to see a restaurant application of this type, so it was fun to see the linked to video.  I have eaten at the Cheesecake Factory a number of times, and when in a business I always look for indications of data gathering and process applications. It is always interesting to see how this can be linked to midsize business needs.

Cheesecake Factory is a global company that serves 80 million guests a year, with over 200 menu items, hardly a small company.  How do they deliver a unique brand experience that meets customer expectations?  In  my own visits I was singularly impressed by their process, though I could not see how they used data to achieve it.  Clearly they had dound out how to deliver quality consistently. This short video and provided a look at the data back of the house.   A chef myself, I wanted to see how big data contributed to the experience.



As every chef knows, its all about the quality assurance of what goes into the food.   They also seek to make the experience as consistent as possible, regardless of the location of the restaurant.  IBM and partner N2N Global  have put together a strategy that provides " ... ERP, Tracebility, Quality and Food Safety, and Business Intelligence Software integrated in a single solution for the Food Supply Chain. ... " 

This is by its nature a big data problem. Multiple sources of supplier information about key ingredients that is being updated constantly. Volatile data because it needs to address such questions as traceability and food safety.  Usage information in each region to assure the highest quality ingredients to meet restaurant specifications.  Feedback from the users of the ingredients to assure continued quality.   Consistent  analysis of costs to assure profits.  That's lots of data, and lots of places where that data can be used to streamline the process. Analytics.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.

Force Feedback for Smartphones

Research ongoing to produce force feedback that could ultimately be used on a smartphone.    This opens some interesting new sensor applications, on games certainly, but also in other areas.

Real Time Shopper Feedback

In Progressive Grocer:  How BJ's is using a real-time shopper feedback system.  " ... BJ's Wholesale Club is using a survey platform from On The Spot Systems that provides real-time feedback from members who use mobile devices to take surveys about private-label products. "Survey On The Spot's real-time, actionable feedback model will allow BJ's to know what its customers are thinking at that most critical moment, while they are actively consuming the products -- allowing the company to make immediate decisions to build stronger relationships with its members," said Ken Kimmel, president of On The Spot ... "

Advancing Analytics to Machine Learning

Things are changing in  advanced analytics.   Simple statistics  is not enough anymore.  An example from Orbitz.  Read the whole article:    "... I lead the traditional statistical modelers as well as the chief scientist and the machine learning (ML) crew. At Orbitz, we have found value in incorporating both types of data mining professionals (machine learners and statistical modelers) because many problems are well-suited for both camps. For example, the statistical modelers effectively address areas such as marketing mix analysis, predictive models across online marketing channels, customer lifetime value models, churn models, credit card fraud models, etc. Similarly, the machine learning staff deploys their algorithms in areas leveraging Big Data, where system feedback is leveraged to quickly learn from patterns in order to self-improve – areas such as the Hotel Recommendation Engine and Hotel Sort  on the Orbitz Web site. ..." 

Blog Experimentation

This blog has been around for a very long time.  Once a mirror for a blog within a large enterprise.  Now in the midst of experimenting with changes in its use and formats.  I have used a number of other social networking capabilities to augment its reach, you will see a line below that allows you to pass the content here out to several of the other most popular social destinations.   I am unsure about the clutter that this introduces, but I like the functionality, which allows me to easily distribute the content. Feel free to experiment and give me your feedback.