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In order top pre-empt and be ready to face further turbulences in the digital age, Soft Bank CEO Masayoshi Son helped create a venture fund with investments from Apple, Foxconn and Qualcomm. This fund has been created to helped start-ups working in the digital world with capabilities in data warehousing and subsequent generation of business insights. A report submitted by research form CB Insights has further helped cement Soft Bank’s reputation as an influencer of investments to tech start-ups. The Soft Bank Vision Fund invested in sixteen deals in the US alone in the just concluded year. This includes firms like Slack, We Work, and Nauto plus the latest involvement in insurance firm Lemonade. In addition, the fund has invested overseas too at places such as London-based Improbable Worlds, China’s Didi Chuxing and India’s Paytm. Beyond just the numbers, the crucial point here is the strategic intent of placing bets with emerging players in various markets.

Source:https://venturebeat.com/2017/12/26/how-softbank-changed-the-venture-capital-game-in-2017/amp/?__twitter_impression=true

Uploaded Date:19 January 2018

Machine learning is now increasingly aiding the healthcare industry by predicting heart disease and diabetes. Billions of dollars could be saved annually if these two chronic diseases could be reduced and managed better. A method has thus been developed by the Framingham Heart Study to look into the possibilities of cardiovascular diseases across the next ten years. The method has already achieved a fifty-six percent accuracy in predicting. This is still lower than the eighty-two managed by the Center for Information and Systems Engineering of the Boston University. One thing hospitals need to rigorously undergo is conduct data warehousing operations for patients’ records. This includes their eating habits, genetic makeup, cholesterol levels, age, weight and blood pressure. Tech giants such as Google are now entering the medical field in a large way by providing machine learning and analytics support. Information on patients gets tracked using medical devices, fitness trackers, smart watches and even mobile phones which store health data.

Source:https://hbr.org/2017/05/how-machine-learning-is-helping-us-predict-heart-disease-and-diabetes

Uploaded Date:10 July 2017

It is now well established that Machine Learning(ML) is going to be a game changer. Chatbots are already impacting a 200 billion dollar industry. Artificial Intelligence (AI) is better known but ultimately a subset of ML. Netflix And Amazon are already reaping the rewards by leveraging Big Data trends of users and customizing content as well as the advertising accordingly. Data from unstructured sources such as text messages, phone calls, videos or images can also be tracked. Using this, search engines provide relevant content and ML can even deduce inferences based on social media usage. Machines are now being used to even manage funds as Black Rock is doing. Authentic business intelligence gets extracted using patterns such as Natural Language Processing (NLP), image categorization and facial recognition as done by Facebook. ML even finds combinations or products purchased together as Amazon is doing using the algorithm of the German firm Otto. External events can be correlated with business information using data on weather, polity, stock markets and government stats.

Source:https://www.forbes.com/sites/forbestechcouncil/2017/06/28/the-machine-learning-imperative/#5e99eeae55d7

Uploaded Date:07July2017 

Machine learning as a concept and its subsequent applicability is constantly on the rise. A three times increase in investments by corporates is expected in Artificial Intelligence (AI) by 2025 when the market will be worth a hundred billion US dollars. Machine learning is utilizing AI concepts to contribute effectively in organizations’ work processes. One such being the increased personalization in customer. Service. Another is by enhancing customer loyalty ultimately leading to more fruitful retention. This is happening because granular data is now available on customer wants and needs, thus marketing strategies can be geared up accordingly. AI is also improving talent recruitment, as the mundane tasks can be delegated to computers allowing humans to focus on the creative side. It is allowing the job profiles to be intricately matched with the applicants’ data. Similarly, major finance activities are getting automated. True business intelligence on the brand’s exposure can be measured through various analytical tools and platforms. Frauds can be detected early on before major harm can be done. The supply chains are also better aligned now thanks to intricate algorithms that can weave past news feeds or social data on obstacles. In the near future, machine learning may also be used in other areas of work such as in career strategizing, retail shelf analysis and asset management with the help of drones or satellites.

Source:https://hbr.org/2017/05/8-ways-machine-learning-is-improving-companies-work-processes?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+harvardbusiness+%28HBR.org%29

Uploaded Date:07/07/2017

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