artificial intelligence

Apple’s new Translate app works offline with 11 languages

Posted by | Apple, Apps, artificial intelligence, Developer, events, Mobile, translate, Translation, wwdc 2020 | No Comments

Translation is an everyday smartphone task for millions of people, but outside a few minor features, Apple has generally ceded the capability to its rivals. That changes today with a new first-party iOS app called, naturally, Translate, which works with 11 languages, no internet connection required.

The app is intended for use with speech or short written sentences, not to translate whole web pages or documents. The interface is simple, with a language selector, text field and record button as well as a few extra widgets like favorites and a dictionary.

At launch Translate will support English, Mandarin Chinese, French, German, Spanish, Italian, Japanese, Korean, Arabic, Portuguese and Russian, with others to come. You simply select a pair of languages and paste or record a snippet of text or audio. The translation should show up immediately.

There’s also a landscape mode that further simplifies the interface:

Image Credits: Apple

The best part is that unlike many translation apps out there, Apple’s is entirely offline, meaning you can use it whether you have a good or bad signal, if you’re out in the middle of nowhere in a country where you don’t get service or if you’re just trying to save data.

There were no specific release details, so the app will probably appear when you upgrade to iOS 14.

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Daily Crunch: Twitter rolls out audio tweets

Posted by | Android, app-store, Apple, apple inc, artificial intelligence, ceo, Daily Crunch, iTunes, machine learning, operating systems, Rahul Vohra, Social, Software, Stockwell, TechCrunch, text messaging, Twitter, United Kingdom | No Comments

Twitter tries to make audio tweets a thing, the U.K. backtracks on its contact-tracing app and Apple’s App Store revenue share is at the center of a new controversy.

Here’s your Daily Crunch for June 18, 2020.

1. Twitter begins rolling out audio tweets on iOS

Twitter is rolling out audio tweets, which do exactly what you’d expect — allow users to share thoughts in audio form. The feature will only be available to some iOS users for now, though the company says all iOS users should have access “in the coming weeks.” (No word on an Android or web rollout yet.)

This feature potentially allows for much longer thoughts than a 280-character tweet. Individual audio clips will be limited to 140 seconds, but if you exceed the limit, a new tweet will be threaded beneath the original.

2. UK gives up on centralized coronavirus contacts-tracing app — switches to testing model backed by Apple and Google

The U.K.’s move to abandon the centralized approach and adopt a decentralized model is hardly surprising, but the time it’s taken the government to arrive at the obvious conclusion does raise some major questions over its competence at handling technology projects.

3. Apple doubles down on its right to profit from other businesses

Apple this week is getting publicly dragged for digging in its heels over its right to take a cut of subscription-based transactions that flow through its App Store. This is not a new complaint, but one that came to a head this week over Apple’s decision to reject app updates from Basecamp’s newly launched subscription-based email app called Hey.

4. Payfone raises $100M for its mobile phone-based digital verification and ID platform

Payfone has built a platform to identify and verify people using data (but not personal data) gleaned from your mobile phone. CEO Rodger Desai said the plan for the funding is to build more machine learning into the company’s algorithms, expand to 35 more geographies and to make strategic acquisitions to expand its technology stack.

5. Superhuman’s Rahul Vohra says recession is the ‘perfect time’ to be aggressive for well-capitalized startups

We had an extensive conversation with Vohra as part of Extra Crunch Live, also covering why the email app still has more than 275,000 people on its wait list. (Extra Crunch membership required.)

6. Stockwell, the AI-vending machine startup formerly known as Bodega, is shutting down July 1

Founded in 2017 by ex-Googlers, the AI vending machine startup formerly known as Bodega first raised blood pressures — people hated how it was referenced and poorly “disrupted” mom-and-pop shops in one fell swoop — and then raised a lot of money. But ultimately, it was no match for COVID-19 and how it reshaped our lifestyles.

7. Apply for the Startup Battlefield

With TechCrunch Disrupt going virtual, this is your chance to get featured in front of our largest audience ever. The post says you’ve only got 72 hours left, but the clock has been ticking since then — the deadline is 11:59pm Pacific tomorrow, June 19. So get on it!

The Daily Crunch is TechCrunch’s roundup of our biggest and most important stories. If you’d like to get this delivered to your inbox every day at around 9am Pacific, you can subscribe here.

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Software will reshape our world in the next decade

Posted by | Alexa, artificial intelligence, augmented reality, blockchain, Column, cryptocurrency, cybernetics, Education, Entertainment, food, Gadgets, iPhone, Opinion, payments, robotics, San Francisco, smartphone, Social, TC, technology, video conferencing | No Comments
Alfred Chuang
Contributor

Alfred Chuang is general partner at Race Capital, an early-stage venture capital firm.

As I was wrapping up a Zoom meeting with my business partners, I could hear my son joking with his classmates in his online chemistry class.

I have to say this is a very strange time for me: As much as I love my family, in normal times, we never spend this much time together. But these aren’t normal times.

In normal times, governments, businesses and schools would never agree to shut everything down. In normal times, my doctor wouldn’t agree to see me over video conferencing.

No one would stand outside a grocery store, looking down to make sure they were six feet apart from one another. In times like these, decisions that would normally take years are being made in a matter of hours. In short, the physical world — brick-and-mortar reality— has shut down. The world still functions, but now it is operating inside everyone’s own home.

This not-so-normal time reminds me of 2008, the depths of the financial crisis. I sold my company BEA Systems, which I co-founded, to Oracle for $8.6 billion in cash. This liquidity event was simultaneously the worst and most exhausting time of my career, and the best time of my career, thanks to the many inspiring entrepreneurs I was able to meet.

These were some of the brightest, hardworking, never-take-no-for-an-answer founders, and in this era, many CEOs showed their true colors. That was when Slack, Lyft, Uber, Credit Karma, Twilio, Square, Cloudera and many others got started. All of these companies now have multibillion dollar market caps. And I got to invest and partner with some of them.

Once again, I can’t help but wonder what our world will look like in 10 years. The way we live. The way we learn. The way we consume. The way we will interact with each other.

What will happen 10 years from now?

Welcome to 2030. It’s been more than two decades since the invention of the iPhone, the launch of cloud computing and one decade since the launch of widespread 5G networks. All of the technologies required to change the way we live, work, eat and play are finally here and can be distributed at an unprecedented speed.

The global population is 8.5 billion and everyone owns a smartphone with all of their daily apps running on it. That’s up from around 500 million two decades ago.

Robust internet access and communication platforms have created a new world.

The world’s largest school is a software company — its learning engine uses artificial intelligence to provide personalized learning materials anytime, anywhere, with no physical space necessary. Similar to how Apple upended the music industry with iTunes, all students can now download any information for a super-low price. Tuition fees have dropped significantly: There are no more student debts. Kids can finally focus on learning, not just getting an education. Access to a good education has been equalized.

The world’s largest bank is a software company and all financial transactions are digital. If you want to talk to a banker live, you’ll initiate a text or video conference. On top of that, embedded fintech software now powers all industries.

No more dirty physical money. All money flow is stored, traceable and secured on a blockchain ledger. The financial infrastructure platforms are able to handle customers across all geographies and jurisdictions, all exchanges of value, all types of use-cases (producers, distributors, consumers) and all from the start.

The world’s largest grocery store is a software and robotics company — groceries are delivered whenever and wherever we want as fast as possible. Food is delivered via robot or drones with no human involvement. Customers can track where, when and who is involved in growing and handling my food. Artificial intelligence tells us what we need based on past purchases and our calendars.

The world largest hospital is a software and robotics company — all initial diagnoses are performed via video conferencing. Combined with patient medical records all digitally stored, a doctor in San Francisco and her artificial intelligence assistant can provide personalized prescriptions to her patients in Hong Kong. All surgical procedures are performed by robots, with supervision by a doctor of course, we haven’t gone completely crazy. And even the doctors get to work from home.

Our entire workforce works from home: Don’t forget the main purpose of an office is to support companies’ workers in performing their jobs efficiently. Since 2020, all companies, and especially their CEOs, realized it was more efficient to let their workers work from home. Not only can they save hours of commute time, all companies get to save money on office space and shift resources toward employee benefits. I’m looking back 10 years and saying to myself, “I still remember those days when office space was a thing.”

The world’s largest entertainment company is a software company, and all the content we love is digital. All blockbuster movies are released direct-to-video. We can ask Alexa to deliver popcorn to the house and even watch the film with friends who are far away. If you see something you like in the movie, you can buy it immediately — clothing, objects, whatever you see — and have it delivered right to your house. No more standing in line. No transport time. Reduced pollution. Better planet!

These are just a few industries that have been completely transformed by 2030, but these changes will apply universally to almost anything. We were told software was eating the world.

The saying goes you are what you eat. In 2030, software is the world.

Security and protection no longer just applies to things we can touch and see. What’s valuable for each and every one of us is all stored digitally — our email account, chat history, browsing data and social media accounts. It goes on and on. We don’t need a house alarm, we need a digital alarm.

Even though this crisis makes the near future seem bleak, I am optimistic about the new world and the new companies of tomorrow. I am even more excited about our ability to change as a human race and how this crisis and technology are speeding up the way we live.

This storm shall pass. However the choices we make now will change our lives forever.

My team and I are proud to build and invest in companies that will help shape the new world; new and impactful technologies that are important for many generations to come, companies that matter to humanity, something that we can all tell our grandchildren about.

I am hopeful.

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IoT solutions are enabling physical distancing

Posted by | 3 D, ambient intelligence, artificial intelligence, Column, coronavirus, COVID-19, e-sports, Education, Entertainment, Extra Crunch, facial recognition, Gaming, Health, IoT, Market Analysis, Sports, Startups, technology, telecommuting | No Comments
Tyler Cracraft
Contributor

Tyler Cracraft is an electronic engineer turned solution architect at Advantech who has more than a decade of experience working in the electronics technology industry.

If you’re a business owner or investor and are wondering about the long-term impacts of the COVID-19 pandemic on the business world, you’re not alone.

Today’s business leaders have been plunged into the deep end of telecommuting with little notice, and the way we do business has been impacted at almost every level. Travel is restricted, meetings are virtual and delivery of goods and even raw materials is being delayed. While some industries that depend on large gatherings are seeing extremely difficult challenges due to the pandemic, others such as the tech industry, see the opportunity and responsibility for innovation and growth.

As many states begin phased reopening, companies are trying to determine what the workplace and business environment will look like in a post-quarantine world. The first obvious step is the integration of personal protective equipment (PPE). Sanitization and face masks will become required and nonessential face-to-face meetings will be a thing of the past, along with shaking hands.

Additionally, relationship-driven careers such as sales and recruiting will have to find new ways to connect to be successful. Physical distancing rules will have to be established, which may include employees coming in alternate days while telecommuting the other days of the week to keep offices at reduced capacity. Large offices of 10 or more may implement thermographic camera technology for fever screening or other real-time technology-based health screenings.

One thing is for sure: IoT devices that enable physical distancing will become an integral part of reopening businesses, facilitating sales connections and embracing a different way of living.

Solutions for physical distancing

There are a variety of IoT devices available that can help business leaders successfully implement physical distancing in their offices. Thermographic camera technology coupled with facial recognition can create a baseline for each employee and then assist in determining if an employee has a temperature outside of their norm. Other remote health monitoring may also take place with healthcare providers, helping employees determine on a daily basis if they are well enough to go into work.

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TinyML is giving hardware new life

Posted by | arduino, artificial intelligence, artificial neural networks, biotech, Cloud, Column, coronavirus, COVID-19, deep learning, drug development, embedded systems, Extra Crunch, Gadgets, hardware, machine learning, manufacturing, Market Analysis, ML, neural networks, Open source hardware, robotics, SaaS, Wearables | No Comments
Adam Benzion
Contributor

A serial entrepreneur, writer, and tech investor, Adam Benzion is the co-founder of Hackster.io, the world’s largest community for hardware developers.

Aluminum and iconography are no longer enough for a product to get noticed in the marketplace. Today, great products need to be useful and deliver an almost magical experience, something that becomes an extension of life. Tiny Machine Learning (TinyML) is the latest embedded software technology that moves hardware into that almost magical realm, where machines can automatically learn and grow through use, like a primitive human brain.

Until now building machine learning (ML) algorithms for hardware meant complex mathematical modes based on sample data, known as “training data,” in order to make predictions or decisions without being explicitly programmed to do so. And if this sounds complex and expensive to build, it is. On top of that, traditionally ML-related tasks were translated to the cloud, creating latency, consuming scarce power and putting machines at the mercy of connection speeds. Combined, these constraints made computing at the edge slower, more expensive and less predictable.

But thanks to recent advances, companies are turning to TinyML as the latest trend in building product intelligence. Arduino, the company best known for open-source hardware is making TinyML available for millions of developers. Together with Edge Impulse, they are turning the ubiquitous Arduino board into a powerful embedded ML platform, like the Arduino Nano 33 BLE Sense and other 32-bit boards. With this partnership you can run powerful learning models based on artificial neural networks (ANN) reaching and sampling tiny sensors along with low-powered microcontrollers.

Over the past year great strides were made in making deep learning models smaller, faster and runnable on embedded hardware through projects like TensorFlow Lite for Microcontrollers, uTensor and Arm’s CMSIS-NN. But building a quality dataset, extracting the right features, training and deploying these models is still complicated. TinyML was the missing link between edge hardware and device intelligence now coming to fruition.

Tiny devices with not-so-tiny brains

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Researchers use biometrics, including data from the Oura Ring, to predict COVID-19 symptoms in advance

Posted by | artificial intelligence, biometrics, biotech, coronavirus, COVID-19, Disease, fatigue, fever, Gadgets, Health, Identification, infection, neuroscience, oura, surveillance, TC | No Comments

A team of researchers from the West Virginia University (WVU) Rockefeller Neuroscience Institute (RNI), along with WVU’s Medicine department and staff from Oura Health have developed a platform they say can be used to anticipate the onset of COVID-19 symptoms in otherwise healthy people up to three days in advance. This can help with screening of pre-symptomatic individuals, the researchers suggest, enabling earlier testing and potentially reducing the exposure risk among front-line healthcare and essential workers.

The study involved using biometric data gathered by the Oura Ring, a consumer wearable that looks like a normal metallic ring, but that includes sensors to monitor a number of physiological metrics, including body temperature, sleep patterns, activity, heart rate and more. RNI and WVU Medical researchers combined this data with physiological, cognitive and behavioral biometric info from around 600 healthcare workers and first responders.

Participants in the study wore the Oura Ring, and provided additional data that was then used to develop AI-based models to anticipate the onset of symptoms before they physically manifested. While these are early results from a phase-one study, and yet to be peer-reviewed, the researchers say that their results showed a 90% accuracy rate on predicting the occurrence of symptoms, including fever, coughing, difficulty breathing, fatigue and more, all of which could indicate that someone has contracted COVID-19. While that doesn’t mean that individuals have the disease, a flag from the platform could mean they seek testing up to three days before symptoms appear, which in turn would mean three fewer days potentially exposing others around them to infection.

Next up, the study hopes to expand to cover as many as 10,000 participants across a number of different institutions in multiple states, with other academic partners on board to support the expansion. The study was fully funded by the RNI and their supporters, with Oura joining strictly in a facilitating capacity and to assist with hardware for deployment.

Many projects have been undertaken to see whether predictive models could help anticipate COVID-19 onset prior to the expression of symptoms, or in individuals who present as mostly or entirely asymptomatic based on general observation. This early result from RNI suggests that it is indeed possible, and that hardware already available to the general public could play an important role in making it possible.

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5G, AI, cybersecurity and renewable energy set for investment boost under EU coronavirus recovery plan

Posted by | 5g, artificial intelligence, digitization, eu, Europe, european commission, european union, GreenTech, Mobile, renewables | No Comments

The European Commission is proposing to direct billions of euros of financial relief into high tech and green investments to help the bloc recover from the coronavirus crisis.

Technologies such as 5G, AI, cloud, cybersecurity, supercomputing and renewable energy look set to benefit from a €750BN pan-EU support package set out today — aligning with the Commission’s pre-existing policy priorities before the pandemic struck the region, causing thousands of deaths and major economic damage.

“Urgent action is needed to kick-start the economy and create the conditions for a recovery led by private investment in key sectors and technologies. This investment is particularly crucial to the success of Europe’s green and digital transitions,” it writes in a factsheet on its budget proposal set out today — which is being slated as a wider “recovery plan” for Europe.

“Investment in key sectors and technologies, from 5G to artificial intelligence and from clean hydrogen to offshore renewable energy, holds the key to Europe’s future,” it adds.

On the green deal front, it’s touting:

  • A massive renovation wave of our buildings and infrastructure and a more circular economy, bringing local jobs;
  • Rolling out renewable energy projects, especially wind, solar and kick-starting a clean hydrogen economy in Europe;
  • Cleaner transport and logistics, including the installation of one million charging points for electric vehicles and a boost for rail travel and clean mobility in our cities and regions;

It also plans to funnel more financial support into a Just Transition Fund to support re-skilling and help businesses tap into the economic opportunities offered by digitization and going green.

The Commission estimates that at least €1.5 trillion will be needed to reboot the EU’s economy as a result of the pandemic crisis in 2020-2021 alone — so the budget proposals include a revision of the 2014-2020 multiannual financial framework as well as a financial framework for the 2021-2027 period.

The Commission is proposing to borrow €750BN on the financial markets, through the issuance of bonds, for a ‘Next Generation EU’ fund which will be channelled through EU programs between 2021 and 2024 — with the loan to be repaid over “a long period of time throughout future EU budgets” (not before 2028 and not after 2058).

It’s proposing three investment pillars for this fund: One focused on support for EU Member States via direct investment and reforms; a second focused on kick starting the EU economy by incentivizing private investments; and a third aimed at learning lessons from the COVID-19 crisis, with a big focus on health, as well as civil contingencies and foreign aid.

Under the first pillar, digital and green technologies are set to benefit from a proposed €560BN Recovery and Resilience Facility that will offer EU Member States financial support for related investments and reforms, including a grant facility of up to €310BN and up to €250BN available in loans.

“Support will be available to all Member States but concentrated on the most affected and where resilience needs are the greatest,” the Commission said today.

It’s also proposing €15BN extra for the European Agricultural Fund for Rural Development — to “support rural areas in making the structural changes necessary in line with the European Green Deal and achieving the ambitious targets in line with the new biodiversity and Farm to Fork strategies”.

Under the second pillar, a new Solvency Support Instrument is intended to mobilize private resources to support what the Commission bills as “viable” European companies in the sectors, regions and countries most affected. It wants this support to be operational from 2020, and is suggesting a budget of €31BN with the aim of aiming to unlock €300BN in solvency support for companies from all economic sectors (to “prepare them for a cleaner, digital and resilient future”, as it puts it).

There’s also more money for the InvestEU investment program which the Commission wants to see hitting €15.3BN over the budget period to spin up more private investment in projects across the EU.

It’s also proposing a new Strategic Investment Facility be built into InvestEU which it wants to generate investments of up to €150BN to boost the resilience of “strategic sectors”, again notably those linked to the green and digital transition — with €15BN set to be chipped in here from the Next Generation EU pot.

Under the third pillar, the Commission is earmarking €9.4BN for a new health programme, EU4Health, that’s intended to strengthen health security and prepare for future health crises.

While the Horizon Europe research program is set to get €94.4BN — including to support what it dubs “vital research” in health, resilience and the green and digital transitions.

Commenting in a statement, European Commission president, Ursula von der Leyen, said: “The recovery plan turns the immense challenge we face into an opportunity, not only by supporting the recovery but also by investing in our future: the European Green Deal and digitalization will boost jobs and growth, the resilience of our societies and the health of our environment. This is Europe’s moment. Our willingness to act must live up to the challenges we are all facing. With Next Generation EU we are providing an ambitious answer.”

In terms of next steps, the Commission’s budget proposals will need to gain political agreement from the European Council. It’s hoping will be achieved by July, with the EU’s executive keen to impress on Member States there’s no time to lose in financing coronavirus relief.

The EU parliament will also need to have its say but the Commission has penciled in early autumn for the adoption of the revised 2014-2020 framework and December 2020 for adoption of the revised Multiannual Financial Framework 2021-2027 (as well as Member States’ Own Resources Decision) — with the aim of implementing the latter framework in January 2021.

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MIT develops a way to use wireless signals from in-home appliances to better understand your health

Posted by | ambient intelligence, articles, artificial intelligence, Gadgets, hardware, Health, IoT, Massachusetts Institute of Technology, MIT, science, TC, technology | No Comments

Having a holistic picture of your health might not mean just wearing a device like an Apple Watch that can monitor your biometrics — researchers at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) have developed a new system that can figure out when and where in-home appliances like hair dryers, stoves, microwaves and washing machines are being used, and they believe that info could help inform healthcare practitioners about the habits and challenges of people under their care.

The researchers devised a system called “Sapple” that uses just two sensors placed in a person’s home to determine use patterns of devices including stoves, hair dryers and more. There’s one location sensor that works using radio signals to figure out placement, with a user able to calibrate it to cover their area by simply walking the bounds of their space. A second sensor measures energy usage through the home, and combines that data with movement information to matching energy use signals with physical locations of specific applicants, to provide data both when a person is using the appliances around the house, and for how long.

This gets around a lot of the issues raised by similar systems, including more simple voltage meters used on their own. While appliances do tend to have specific energy use patterns that mean you can identify them just based on consumption, it’s hard to tell when and how they’re being used with that data on its own. This info can let health professionals know if a patient is taking proper care of hygiene, food preparation and intake and more.

Of course, the system does sound like one that has a lot of potential privacy pitfalls, but its intended use is for specific cases, like providing supervised care of aging populations that need it while also still preserving resources and enabling better distancing, which is actually a more urgent need right now as we continue to figure out how to address caregiving in the context of the COVID-19 pandemic.

It’s a clever system in that it doesn’t require any special smart IoT devices to work, beyond the two simple sensors, and essentially also doesn’t require any technical expertise on the part of the patients receiving care.

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The future of deep-reinforcement learning, our contemporary AI superhero

Posted by | artificial intelligence, Column, deep-reinforcement learning, Extra Crunch, Gaming, Market Analysis, robotics, science | No Comments
Rish Joshi
Contributor

Rish is an entrepreneur and investor. Previously, he was a VC at Gradient Ventures (Google’s AI fund), co-founded a fintech startup building an analytics platform for SEC filings and worked on deep-learning research as a graduate student in computer science at MIT.

It was not long ago that the world watched World Chess Champion Garry Kasparov lose a decisive match against a supercomputer. IBM’s Deep Blue embodied the state of the art in the late 1990s, when a machine defeating a world (human) champion at a complex game such as chess was still unheard of.

Fast-forward to today, and not only have supercomputers greatly surpassed Deep Blue in chess, they have managed to achieve superhuman performance in a string of other games, often much more complex than chess, ranging from Go to Dota to classic Atari titles.

Many of these games have been mastered just in the last five years, pointing to a pace of innovation much quicker than the two decades prior. Recently, Google released work on Agent57, which for the first time showcased superior performance over existing benchmarks across all 57 Atari 2600 games.

The class of AI algorithms underlying these feats — deep-reinforcement learning — has demonstrated the ability to learn at very high levels in constrained domains, such as the ones offered by games.

The exploits in gaming have provided valuable insights (for the research community) into what deep-reinforcement learning can and cannot do. Running these algorithms has required gargantuan compute power as well as fine-tuning of the neural networks involved in order to achieve the performance we’ve seen.

Researchers are pursuing new approaches such as multi-environment training and the use of language modeling to help enable learning across multiple domains, but there remains an open question of whether deep-reinforcement learning takes us closer to the mother lode — artificial general intelligence (AGI) — in any extensible way.

While the talk of AGI can get quite philosophical quickly, deep-reinforcement learning has already shown great performance in constrained environments, which has spurred its use in areas like robotics and healthcare, where problems often come with defined spaces and rules where the techniques can be effectively applied.

In robotics, it has shown promising results in using simulation environments to train robots for the real world. It has performed well in training real-world robots to perform tasks such as picking and how to walk. It’s being applied to a number of use cases in healthcare, such as personalized medicine, chronic care management, drug discovery and resource scheduling and allocation. Other areas that are seeing applications have included natural language processing, computer vision, algorithmic optimization and finance.

The research community is still early in fully understanding the potential of deep-reinforcement learning, but if we are to go by how well it has done in playing games in recent years, it’s likely we’ll be seeing even more interesting breakthroughs in other areas shortly.

So what is deep-reinforcement learning?

If you’ve ever navigated a corn maze, your brain at an abstract level has been using reinforcement learning to help you figure out the lay of the land by trial and error, ultimately leading you to find a way out.

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