How Accounts Can Future-Proof Their Careers In The Era Of Artificial Intelligence

How Accounts Can Future-Proof Their Careers In The Era Of Artificial Intelligence

  • Many of these same experts point to the human experience as a key differentiator for accountants.
  • Many people and businesses have unique needs that first or second generation AI will be unable to understand.
  • Accountants today have the power to define the future of the profession.
  • The industry must develop the ability to adapt and evolve, as well as become proactive about the needs of tomorrow’s clients.
  • Accounting as a profession needs to change, providing consultation and guidance to help clients prepare for and meet the future.

How Accounts Can Future-Proof Their Careers In The Era Of Artificial Intelligence
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Chinese firms fight to lure top artificial intelligence talent from Silicon Valley

Chinese firms fight to lure top artificial intelligence talent from Silicon Valley

  • Before each job interview, Alex Ren offers the following advice to his clients to ensure their success: “Be humble and appreciate the opportunity to fully demonstrate your strength and what you can offer”.
  • The advice is not for potential employees.
  • Rather, it is for Chinese technology companies trying to hire top-tier Silicon Valley talent in artificial intelligence (AI) in competition with the likes of Alphabet, Uber Technologies and Facebook.
  • “Chinese companies are obsessed with hiring Silicon Valley talent because winning talent here is like reaching the commanding heights of the AI battlefield,” said Ren, founder of TalentSeer, a San Francisco-based headhunting company focused on AI expert recruitment.

Chinese firms fight to lure top artificial intelligence talent from Silicon Valley
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Notable Fundraising Highlights of Machine Learning Startups in 2016

Notable Fundraising Highlights of #MachineLearning Startups in 2016

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  • 2016 has been a prolific year for Machine Learning/AI companies in all fronts.
  • In the post I have tried to capture some notable funding rounds and acquisitions of Machine Learning (ML) startups that took place last year.
  • Deep Learning (DL) companies that can help their clients run more successful marketing campaigns are highly valued.

2016 has been a prolific year for Machine Learning/AI companies in all fronts. In this post I have tried to capture some notable funding rounds and acquisition…
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Banks turn to AI for improved customer service, competitive edge

Banks turn #AI for improved customer service, competitive edge  #custserv #fintech

  • com: Banks find big innovation payoff in hackathons ]
  • With the Wells Fargo fake accounts scandal fresh on your mind, it’s hard to feel sorry for banks these days.
  • Payment services like PayPal and investment services like Wealthfront are competing for the clients that banks used to take for granted.
  • ‘s a look at what three banks – Capital One, RBS and TD Bank – have learned from adopting AI.
  • Artificial intelligence may prove to be a key part of the solution for banks seeking to remain competitive.

How Capital One, RBS and TD Bank use artificial intelligence to boost customer service and revenue.
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​#CXOTALK Reinventing the legal industry with AI, machine learning, and augmented reality

My latest:: Reinventing the legal industry w #AI, machine learning, and augmented reality

  • In the short clip embedded above, Shea explains why the firm invests in knowledge management, artificial intelligence, machine learning, and augmented reality.
  • 80 percent of the law firms surveyed see digital strategy as critical
  • Law firms must respond to the changing demands of consumers just as companies do in other industries.
  • The legal industry has a reputation for being slow to change and behind the curve on adopting new technologies.
  • The firms that adopt and change and innovate will be the haves and the have-nots in the industry.

The CIO for a $2 Billion law firm explains how his organization responds to changing customer expectations with the most modern technology available.
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GitHub

Very interesting code, lda2vec tools for interpreting natural language  #machinelearning #NLP

  • We build a model that builds both word and document topics, makes them interpreable, makes topics over clients, times, and documents, and makes them supervised topics.
  • lda2vec also yields topics over clients.
  • lda2vec the topics can be ‘supervised’ and forced to predict another target.
  • It’s research software, and we’ve tried to make it simple to modify lda2vec and to play around with your own custom topic models.
  • LDA on the other hand is quite interpretable by humans, but doesn’t model local word relationships like word2vec.

Read the full article, click here.


@andradeandrey: “Very interesting code, lda2vec tools for interpreting natural language #machinelearning #NLP”


Contribute to lda2vec development by creating an account on GitHub.


GitHub