Weekly Review 16 May 2017

Below are some of the interesting links I Tweeted about recently.

1. Ten ways AI is being used in retail: https://www.techemergence.com/artificial-intelligence-retail-10-present-future-use-cases/
2. Using machine learning to detect lung cancer in x-rays: https://techcrunch.com/2017/05/08/chinese-startup-infervision-emerges-from-stealth-with-an-ai-tool-for-diagnosing-lung-cancer/ 
3. We are in the golden age of AI: https://finance.yahoo.com/news/golden-age-solving-problems-were-093919934.html
4. Automation technology, including AI, is going to wipe out a lot of entry-level legal jobs: https://www.axios.com/artificial-intelligence-is-coming-for-law-firms-2394154251.html
5. Microsoft is offering a deep learning service in Azure: https://techcrunch.com/2017/05/10/microsoft-launches-a-new-service-for-training-deep-neural-networks-on-azure/ 
6. How to select the optimal number of clusters: http://www.kdnuggets.com/2017/05/must-know-most-useful-number-clusters.html 
7. The effect of AI on employment-only highly-educated people are really safe at the moment: http://www.techrepublic.com/article/why-automation-in-the-age-of-ai-will-change-the-way-we-think-of-work/ 
8. Processing job descriptions with deep learning ANN: http://www.kdnuggets.com/2017/05/deep-learning-extract-knowledge-job-descriptions.html 
9. Summarising text using reinforcement learning: https://techcrunch.com/2017/05/11/salesforce-aims-to-save-you-time-by-summarizing-emails-and-docs-with-machine-intelligence
10. TensorFlow seems to be a bit tricky to use: http://www.theregister.co.uk/2017/05/12/tensor_flow_hands_on/ 
11. Detecting network anomalies-that is, security threats-using machine learning: https://techcrunch.com/2017/05/12/las-vegas-taps-ai-for-cybersecurity-help/ 
12. My SECoS algorithms (http://ecos.watts.net.nz/Algorithms/SECoS.html) have also been applied to this sort of thing: https://techcrunch.com/2017/05/12/las-vegas-taps-ai-for-cybersecurity-help/
13. Twitter is finding tweets relevant to users using deep neural networks: https://www.datanami.com/2017/05/10/twitter-ranking-tweets-machine-learning/ 
14. Some future trends and developments in AI: http://www.datasciencecentral.com/profiles/blogs/a-sneak-peek-at-the-future-of-artificial-intelligence-the-newes-1 
15. Tools to automate the construction of deep learning models: https://www.enterprisetech.com/2017/05/10/automation-automation-ibm-powerai-tools-aim-ease-deep-learning-data-prep-shorten-training/ 
16. Biased models come from biased data, but biased data is ruining people's lives: https://www.theregister.co.uk/2017/05/08/algorithmic_bias/ 
17. It doesn't matter how good the algorithm is, if you don't put good data into it, you won't get a good model out if it. This is basic stuff.
18. Personally I would classify deep learning as computational intelligence, but that would further confuse journalists: https://techcrunch.com/2017/05/14/pattern-recognition/ 
19. A lot of academic success also seems to come from shameless self-promotion: http://www.techrepublic.com/article/the-it-leaders-guide-to-shameless-self-promotion-part-1/
20. The two phases of gradient descent in deep learning: http://www.kdnuggets.com/2017/05/two-phases-gradient-descent-deep-learning.html 
21. Using AI to detect abuse in mental health group chats: https://techcrunch.com/2017/05/15/sunrise-health/ 
22. Facebook's platform for researching conversational AI chatbots: https://www.theverge.com/2017/5/15/15640886/facebook-parlai-chatbot-research-ai-chatbot 
23. Before data mining, make sure that you have the legal right to mine the data you are looking at: https://techcrunch.com/2017/05/15/deepmind-nhs-health-data-deal-had-no-lawful-basis/ 
24. THAT won't cause security problems.... http://www.techrepublic.com/article/delta-testing-facial-recognition-for-self-service-bag-check-in-at-minneapolis-airport/