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In the news this week, All the Member states of the UN Educational, Scientific and Cultural Organization (UNESCO) adopted a historic agreement that defines the common values and principles needed to ensure the healthy development of AI.

Welcome to The Digital Eye, your weekly roundup of the latest technology news. 

Our team of experts have scoured the internet for the most exciting and informative articles so that you can stay up-to-date on all things digital, data, blockchain, AI & analytics.

This week’s the Top Reads:

  1. Ethics of Artificial Intelligence
  2. A Golden Age For Natural Language
  3. Top Machine Learning Startups that Aim to Excel in 2022
  4. Building AI: staffing the most challenging part
  5. Top 10 Applications of Data Science In Insurance Sector

Bonus Article:

  1. VIDEO: What can we do to improve work performance?

 

We hope you find this information valuable and would appreciate your help in sharing it with others who may also be interested.


 

Ethics of Artificial Intelligence

 

193 countries to adopt a first global agreement
“Decisions impacting millions of people should be fair, transparent & contestable. New tech must help us address major challenges”

 

Ethics of Artificial Intelligence

 👁️‍🗨️ Read Article

 

“All the Member states of the UN Educational, Scientific and Cultural Organization (UNESCO) adopted on Thursday a historic agreement that defines the common values and principles needed to ensure the healthy development of AI.

Artificial intelligence is present in everyday life, from booking flights and applying for loans to steering driverless cars. It is also used in specialized fields such as cancer screening or to help create inclusive environments for the disabled.”

shared by @dev_discourse

 


 

A Golden Age For Natural Language

 

NLP is branch of machine learning that endows computers with human-like ability to understand text & spoken word.
READ: Incumbents are taking advantage of uneven playing field.

 

A Golden Age For Natural Language

👁️‍🗨️ Read Article

 

“Every company talks to its customers with natural language. The last three years signalled the beginning of a golden age for natural language processing (NLP), one of the most useful and visible forms of machine learning (ML).

NLP is a branch of machine learning that endows computers with the human-like ability to understand the text and spoken word. Thanks to the increase in computational power, the sheer volume of raw language data available on the Internet, and the popularization of deep learning, NLP has transformed from a hypothetical question posed in the 1950 Turing Test to everyday reality.”

 

shared by @Forbes


 

Top Machine Learning Startups that Aim to Excel in 2022

 

ONES TO WATCH:
@algorithmia
@avora
@Cogninoai
@Databand_ai
@indicoData
@netrainc
@particle

 

Top Machine Learning Startups that Aim to Excel in 2022

👁️‍🗨️ Read Article

 

“From very limited usage in the business world before 2012, machine learning dependency has gone up exponentially since the boom. Today there are 9k+ machine learning startups and companies according to Crunchbase. Here are the top machine learning start-ups that aim to excel in 2022.”

shared by @analyticsinme


 

Building AI: staffing the most challenging part

 

Machine learning projects are much more complicated than ML model algorithms. Be ready to build a robust team to take care of machine learning operations

 

Building AI: staffing the most challenging part

👁️‍🗨️ Read Article

 

“Every company worth its weight is set on achieving practical and scalable artificial intelligence and machine learning. However, it’s all much easier said than done — to which AI leaders within some of the most information-intensive enterprises can attest. For more perspective on the challenges of building an AI-driven organization, we caught up with Jing Huang, senior director of engineering and machine learning at Momentive (formerly SurveyMonkey), who shares the lessons being learned as AI and ML are rolled out.”

shared by @ZDNet @joemckendrick


 

Top 10 Applications of Data Science In Insurance Sector

 

TOP FIVE:
1. Fraud detection
2. Personalised marketing
3. Insurance pricing
4. Customer acquisition
5. Risk assessment

 

Top 10 Applications of Data Science In Insurance Sector

👁️‍🗨️ Read Article

 

“The amount of data generated every single day is something that goes beyond our imagination. The data generated has significance and can be transformed in a manner that is useful. This is where data science comes into play. Data science is the art of making the best of data so that businesses can better understand their customers, their expectations and work in every possible manner to meet them. With the ability of data science to transform raw data into meaningful ones, it has gained immense popularity in almost all the sectors that one can think of. The insurance sector is one such sector that relies on data science heavily. Here are the top 10 applications of data science in the insurance sector. Have a look!”

shared by @analyticsinme


 

Bonus Article

 

VIDEO: What can we do to improve work performance?

 

Noise in decision making can lead to an error in human judgement, which results in inconsistent performance levels. Data science could be the answer.

 

VIDEO: What can we do to improve work performance?

👁️‍🗨️ Watch

 

Take a look and please let me know what you think

 


 

The Digital EyeThe DiGITAL EYE