Tuesday, April 24, 2018
So what is 5G? Who are the leaders? What does it mean for jobs?
Sunday, April 22, 2018
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.
- What is the science?
- What is the technical risk?
- Is it innovative?
- 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
- improvements in data access and data volume,
- improvements in model accuracy, and ultimately
- 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?
Friday, April 20, 2018
Monday, April 16, 2018
Facial recognition to track citizens. A MUST read!
- 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.
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
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 Abrà moff 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.