The key Areas where AI is focussing on

Where does your texhnology, app, project fit in?

5 Attributes you need to look at when building an AI model or App - to claim an R and D tax rebate

A major issue in claiming an R and D tax deduction is to mapping the language that the government defines as r and d to your project. 

1. What is the science?
2. What is the technical risk?
3. Is it innovative? 
4. What testing have you done? 

And the list goes on 

The reality is that most software projects and ongoing developments of software and apps should be defined as R and D . It all about the interpretation and justification - and the key is to be able to document and justify your project as an r and d one....because I believe that anything can be justified, and the intention is that the government wants to encourage companies to continue to innovate - 

Because innovation is the food for growth! 

Everyone is talking AI and machine learning..... is an app just a microcosm of a larger machine learning AI model? 

So, what makes AI or an app useful?  It’s all about how data in the model is used.

An AI model is a way of looking at data - as data changes, the AI model nnneds to adapt accordingly - 

An AI system needs to be built with five attributes in mind says Dinesh Nirmal - vice president of analytics development at IBM. 

1. Managed

The AI and machine learning model needs to have  thoughtful, durable, and transparent infrastructure. 

That starts with identifying the data pipelines and correcting issues with bad or missing data. There needs to be a methodology of integrating  data governance and version control for models. The version of each model — and their might be thousands of them concurrently needs to clearly  indicates its inputs - 

where the data came from needs to be known 

2. Resilient

Being fluid means accepting that models will fall out of sync. That “drift” can happen quickly or slowly depending on what’s changing in the real world. Regression testing needs to be done on a regular basis. .

Accuracy thresholds need to be defined and and automatic alerts to let you know when the model need attention. 

Will you need to retrain the model on old data, acquire new data, or re-engineer your features from scratch? The answer depends on the data and the model.

Before trying to find the problem, one needs to look at defining the problem.

3. Performance 

The AI model needs to compute the transactions in milliseconds, not minutes, to gain a competitive advantage and make the system work. 

Optimum performance is key 

The AI model needs to run fast and error-free regardless of where you deploy it on premises , or in the cloud.

4. Measurable

The results and outputs need to be clearly measured and have adequate reports. 

When starting the project , visualize how you are going to report what you’re learning and how it changes.

What you can measure you can manage - think about how you can easily report on short , medium and long term goals 

Some Kpis 

1. improvements in data access and data volume,
2. improvements in model accuracy, and ultimately
3. improvements to the bottom line.

5. Continuous

The AI model needs to change and continuously learn as the world changes. The Ai model needs to be continuously evaluated and retrained to adapt to a changing world. 

Jupyter and Zeppelin notebooks that can plug into processes for scheduling evaluations and retrain models are useful tools to use 

You will gain an understanding of absorbing  the advantages and limitations of the algorithms, languages, datasets, and tools that are being used. 

Fluid AI demands continuous improvement for data, tools, and systems, but also continuous improvement from the team. 

Data science is a journey. Pay attention to these five attributes and you’ll bring focus to each moment and force yourself to find clarity about the future.

The data will never sit still, but would you really want it any other way?

Internet of things - Evolution or Revolution

Facial recognition to track citizens. A MUST read!

The Bob Pritchard Column

In just 2 years, there will be 570 million surveillance cameras — that's nearly one camera for every two citizens.  At the same time, China is a building a national database that will recognize any citizen within three seconds. Thanks to a large population and minimum privacy laws, police and private companies have led the way in developing surveillance technology that is now being used to track travel, shopping, crime, and even toilet paper usage.

 

 

These are some of the ways people's faces are being used for surveillance:

• One of the most common facial recognition programs is Face++ which is used to manage entry everywhere from Beijing's train stations to Alibaba's office building.
• Alibaba has also developed its own systems that will soon be used in Shanghai's metro to identify commuters via their face and voice
• Facial recognition cameras are installed at intersections to take pictures of people crossing roads or offending traffic rules.
• Railway police already use facial recognition sunglasses that can identify travelers within 100 milliseconds. Since their introduction earlier this year, they've been used to identify a number of criminals.
• A number of provinces photograph jaywalkers and, after its matched to a police database, post the photo, ID number and home address on public screens. Offenders can spend 20 minutes helping a traffic officer or pay a $3 fine to have the image removed.
• College entrance exams across the country use facial and fingerprint recognition to ensure test takers are the real students.
• After a spate of kidnappings, some childcare centers only unlock doors to faces registered in its system. One kindergarten has more than 200 security cameras as well as a police station on campus.
• Even toilet paper dispensers use the technology, limiting each person to 2 feet of paper every nine minutes. Apparently a number of patrons kept stealing from public bathrooms.
• KFC store uses "Smile to Pay" technology.
• Customers can also use facial recognition to pay for purchases at unmanned convenience stores
• Alibaba has a chain of cashless stores called Hema. Shoppers use their face and phone number to approve payments from their Alipay account.
• Customers of China Merchants Bank scan their faces instead of their bank cards at some 1,000 ATMs.
• Xiaozhu, the Airbnb of China, has smart locks that open after scanning renters' faces
• A car vending machine by Alibaba's Tmall even uses state-of-the-art recognition technology.
• Insurance firm Taikang verifies the identities of customers by their face
• Police in Chongqing use surveillance software and in the first 40 days, it identified 69 criminals
• SenseTime's software tracks customers as they move around a department store.
• Xinjiang has more than 40,000 surveillance cameras used to track and monitor the Uyghur ethnic minority.
• To enter the Hotan bazaar in Xinjiang, shoppers must have their face scanned and cross-referenced to their national identification card.
• Even petrol stations in Xinjiang require drivers be identified by facial recognition cameras before filling up.
• In other areas of China, police use hand-held systems to recognize faces.
• Police in Kashgar now have smartphones that scan faces and match with IDs
• China’s Police have an SUV with a 360-degree camera that can scan every face within 200 feet while driving up to 75mph. The driver is alerted to any database match.

Anyone still think we are winning the technology race?

AI device for diabetic eye problems approved by FDA

IDx-DR can diagnose diabetic retinopathy, the most common cause of vision loss among the more than 30 million Americans living with diabetes 

By Angela Chen@chengela  Apr 11, 2018, 1:25pm EDT from the verge 

 

The US Food and Drug Administration has approved an artificial intelligence diagnostic device that doesn’t need a specialized doctor to interpret the results. The software program, called IDx-DR, detects a form of eye disease called diabetic retinopathy by looking at photos of the retina.

Diabetic retinopathy (although rare)  is the most common vision complication for more than 30 million Americans living  with diabetes 

Photos are taken by a retinal camera of the patient’s retina are uploaded to IDx-DR  and an algorithm analyzes the images to determine whether the patient has the disease , where too much blood sugar damages the blood vessels in the back of the eye. 

In one clinical trial that used more than 900 images, IDx-DR correctly detected retinopathy about 87 percent of the time, and could correctly identify those who didn’t have the disease about 90 percent of the time. 

The software is unique because it’s autonomous and there’s “not a specialist looking over the shoulder of [this] algorithm,”

 IDx-DR founder Michael Abràmoff told Science News. “It makes the clinical decision on its own.” This means that the technology can be used by a nurse or doctor who’s not an eye specialist, making diagnosis more accessible. 

The benefit..... over 30 million patients wouldn’t need to wait for an eye specialist to be available to get a diagnosis...

There will always be a need for a specialist to check and be responsible when the diagnosis is wrong - but that specialist can be a technician that can check lots - creating other jobs 

Now that the FDA has cleared IDx-DR, it might lead the way to a new slew of autonomous diagnostic tests and the trade-offs they bring. Such as Googles  DeepMind which is using  AI to spot eye disease. 

Cities launching their own Cryptos

The Bob Pritchard Column

Seoul, the capital city of South Korea will soon use a city-funded cryptocurrency called S-Coin for everything from subway rides to kids’ allowances. This is part of a master plan to create a comprehensive blockchain bureaucracy in Seoul.

 

As recently as a couple of months ago, South Korea vocally opposed blockchain for a number of reasons, not the least of which was a fear that North Korea would hack it, and they went  as far as considering taxing crypto-speculation and banning crypto accounts for minors.

 

 

But South Koreans are the biggest crypto-consumers after Japanese and Americans, and Korean crypto-startups raise $89m a month. So as coin-trading hysteria subsided, Seoul hired Samsung’s enterprise IT consultancy in November 2017 to coin their crypto dreams a reality. 

 

As Seoul is the world's leading city in the field of information and communications, they are studying new technologies such as blockchains. S-Coin will be very useful as a payment means in the Korean capital which will help in the funding of public welfare programs or even for compensation of private contractors.

 

The initiative is part of the city’s Blockchain master plan which will help the city publish regulatory guidelines on digital currencies and also devote public resources towards the growing blockchain development sector. On implementation, Seoul will become the largest city to adopt its own digital currency.  The city will be following footsteps of Dubai which is already developing a blockchain digital currency known as emCash which will act as a legal tender for both private and public debts.

 

Other cities which have also floated the aim of using their own digital currencies include Berkeley and CA which are aimed at tokenizing municipal bonds.  The move to join the growing cryptocurrency market has also seen several governments come in like the case with Venezuela which developed its own cryptocurrency called Petro. More to that the Islands of Antigua and Barbuda are already working towards developing their own cryptocurrency exchange platform. In general, many governments are working towards using blockchain to digitize their own fiat currencies.

 

Many countries are preferring digital currencies to reduce their reliance on the US dollar with Marshal Islands developing their own cryptocurrency to avoid the reliance on the dollar.

 In the meantime - here is a map of current landscape

Solve this and win a Nobel Prize

How do the trillions of cells that make up your body stay in touch? Apparently The same way we used to: 

sending notes through the post.

Learning how to read and write “letters” and post them through our intra-body postal system running through our blood, could give us early warning about cancer and Alzheimer’s and potentially finding a cure!!

What we need to do is to work out how to read the mail,  says University of Sydney associate professor Wojciech Chrzanowski, and understand our bodies at a cellular level.

This is how the Prof says it works :- 

All the cells in our body are constantly producing tiny bubbles which the body (or something) fills with a cocktail of DNA and other molecules and are sent into the bloodstream. 

These cells are called extracellular vesicles 

These Cells have special receptors to read the data in the bubbles. The data lets cells send messages to each other. 

Those messages can tell our body what to do.

Professor Chrzanowski is particularly interested in the Stem cells that heal damaged tissue – without physically touching the damage. 

He theorises they are sending out tiny bubbles filled with DNA. When the damaged cell receives the bubble, it follows the DNA instructions and heals itself.

Professor Chrzanowski and teams at the CSIRO are trying to decipher and potentially write or code those messages. 

Imagining being able to inject these regenerating cells into patients with cancer or autoimmune conditions.

It’s like force-feeding the body a message that says: heal thyself.

Want to win a Nobel prize? 

All we need to do is work out how to read the mail.

“You could envisage this cellular system as a post office system – a letter is sent from one cell to another. And the letters contain programs for the cells to run,” says University of Sydney associate professor Wojciech Chrzanowski.

We still don’t quite know how the system works – “If we can figure that out, we’ll probably win a Nobel, to be honest,” says Professor Chrzanowski – but here’s how the leading theory goes

HOw we are trying to solve the puzzle 

This is how Professor Chrzanowski and doctoral candidate Sally Yunsun Kimthey have been learning to read these letters .....

The pair warmed a group of extracellular vesicles with a laser, and then measured their vibrations using a tiny needle about 100,000 times thinner than a human hair.

Hot molecules vibrate at different rates depending on what they are made of. By measuring the vibration, the team could tell exactly what was in each bubble.

It was like reading someone else’s mail without ever opening it.

“This is going to be a pretty important development,” says Professor Andrew Hill, president of the International Society for Extracellular Vesicles.