This AI Technology Week shares how with the advent of neural network models for NLP, the focus of feature engineering is shifted towards model architecture engineering. The use of neural networks allowed features to be learned while the models were being trained. Whereas, A team from DeepMind and Google Research used neural networks to automatically create efficient heuristics from a collection of MIP examples in the new study Solving Mixed Integer Programs (MIP) Using Neural Networks.

Companies are increasingly depending on artificial intelligence to streamline the hiring process through job-matching platforms and AI-powered games and interviews. Moreover, At the Tokyo Olympic Games 2020, national Olympic teams will use machine learning to gain an advantage over their competitors. As from the tech startups: Fenix, a micro-mobility firm, paid $5 million for Palm, a shared e-scooter company in Turkey.

10) Prompt-based learning can make language models more capable

Supervised learning, where AI models are trained on input data annotated for a particular output until they can detect the underlying relationships between the inputs and outputs, plays a major role in natural language processing (NLP).

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9) DeepMind & Google Use Neural Networks to Solve Mixed Integer Programs

A team from DeepMind and Google Research leverages neural networks to automatically construct effective heuristics from a dataset for mixed integer programming (MIP) problems. The approach significantly outperforms classical MIP solver techniques.

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Read More: Synced Review

8) E-scooter company Fenix acquires Palm for $5M, gains entry to the Turkish market

E-scooter company Fenix acquires Palm for $5M, gains entry to the Turkish market. According to TechCrunch Abu Dhabi-based micro-mobility company, Fenix has acquired Palm, a shared e-scooter company in Turkey, for $5 million – the precise amount the corporate raised last November and this past February during its seed round.

E-scooter company Fenix acquires Palm for $5M, gains entry to Turkish market

Read More: Automeme

7) Looking for work? Here’s how to write a résumé that an AI will love.

Through job-matching platforms and AI-powered games and interviews, companies are relying more and more on artificial intelligence to streamline the hiring process. But some job seekers feel frustrated and misunderstood by these technologies.

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Read More: MIT Technology Review

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6) Machine Learning Technologies at Tokyo 2020 Olympics

National Olympic teams are using machine learning to gain an edge in competition over their opponents at the Tokyo Olympic Games 2020.

Machine learning technologies are being used at international sports events from athlete data tracking, coaches’ real-time feedback that can tell athletes when to train and when to stop, to predicting sports injuries with algorithms.

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Read More: InfoQ

Author: Daniel Dominguez

5) Researchers turn the spotlight on the hidden workers of the cybercrime world

Phishing schemes, malware campaigns, and other operations involve an array of workers beyond the criminal masterminds. Could giving them better opportunities for legitimate work help cut crime?

Read More: ZDNet

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4) Artificial intelligence is bringing the dead back to ‘life’ — but should it?

In recent years, technology has been employed to resurrect the dead, mostly in the form of departed celebrities. Carrie Fisher was digitally rendered to reprise her role as Princess Leia in the latest “Star Wars” film.

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Read More: UCR News

3) How to do machine learning without an army of data scientists

The artificial intelligence/machine learning software development and deployment lifecycle are still very nascent. The challenge of moving models into production is exacerbated by demand for speed and a shortage of qualified ML engineers. But there’s hope that things may soon get better.

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Read More: Tech Republic

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2) LinkedIn says it reduced bias in its connection suggestion algorithm

In a blog post today, LinkedIn revealed that it recently completed internal audits aimed at improving People You May Know (PYMK), an AI-powered feature on the platform that suggests other members for users to connect with.

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Read More: Venture Beat

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1) AI-driven knowledge management – Why it matters to contact centers and how they can achieve it

The Austrian management consultant, Peter Drucker said: “knowledge has become the resource rather than a resource…”. Certainly, knowledge management is at the heart of the contact center’s role, bridging the gap between customers’ inquiries and the facts, which will resolve their problems. But it is not just an important challenge, it’s a very difficult one.

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Read More: Tech Native