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GitHub Copilot and the Rise of AI-Language Models in Programming Automation

GitHub Copilot

Should I Use Github Copilot?

If you are a software engineer or count any of them among your circle of acquaintances, then you're probably already aware at some level of Copilot. Copilot is GitHub's new deep learning code completion tool.

Autocomplete tools for programmers are nothing new, and Copilot is not even the first to make use of deep learning nor even the first to use a GPT transformer. After all, TabNine sprung out of a summer project by OpenAI alum Jacob Jackson and makes use of the GPT-2 general purpose transformer.

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How to Train a Joint Entities and Relation Extraction Classifier Using BERT Transformer With spaCy 3

Train a Joint Entities and Relation Extraction Classifier

Photo by JJ Ying on Unsplash.

Introduction

One of the most useful applications of NLP technology is information extraction from unstructured texts — contracts, financial documents, healthcare records, etc. — that enables automatic data query to derive new insights. Traditionally, named entity recognition has been widely used to identify entities inside a text and store the data for advanced querying and filtering. However, if we want to semantically understand the unstructured text, NER alone is not enough since we don't know how the entities are related to each other. Performing joint NER and relation extraction will open up a whole new way of information retrieval through knowledge graphs where you can navigate across different nodes to discover hidden relationships. Therefore, performing these tasks jointly will be beneficial.

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Building an Intelligent News Recommendation System Inside Sohu News App

With 71% of Americans getting their news recommendations from social platforms, personalized content has quickly become how new media is discovered. Whether people are searching for specific topics or interacting with recommended content, everything users see is optimized by algorithms to improve click-through rates (CTR), engagement, and relevance. Sohu is a NASDAQ-listed Chinese online media, video, search, and gaming group. It leveraged Milvus, an open-source vector database built by Zilliz, to build a semantic vector search engine inside its news app. This article explains how the company used user profiles to fine-tune personalized content recommendations over time, improving user experience and engagement.

Recommending Content Using Semantic Vector Search

Sohu News user profiles are built from browsing history and adjusted as users search for, and interact with, news content. Sohu’s recommender system uses semantic vector search to find relevant news articles. The system works by identifying a set of tags that are expected to be of interest to each user based on browsing history. It then quickly searches for relevant articles and sorts the results by popularity (measured by average CTR), before serving them to users.

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Does Observability Throw You for a Loop?

Our new mantra for managing and maintaining the health and functionality of our apps and environments is observability. Observability is the quality of software, services, platforms, or products that allows us to understand how systems are behaving. Without the new sources of data giving us insights, our modern cloud-native applications would be quite a challenge to monitor. Observability, that deep data, is the new fuel for our developer and DevOps engineers.

The duality of observability is controllability. Observability is the ability to infer the internal state of a 'machine' from externally exposed signals. Controllability is the ability to control input to direct the internal state to the desired outcome. While driving, observing a red stoplight means controlling our vehicle by pressing the breaks (or in some modern vehicles, having the brakes applied automatically for us).

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How Low-Code Platforms Implement Complex Business Processes

If a low-code development platform wants to implement complex business processes, the following conditions must be met.

1. What Is Automation?

There are two main types of automation. The difference comes mainly from AI, which is based on the benefits of the upcoming technology. For example, it generates digital data, which is the driving force of machine learning.
Automation is the key to improving efficiency, reducing human error and reducing operating costs. Repetitive work will require fewer workers, and more employees will focus on strategic decision-making and creative problem solving.

2. The 2 Types of Automation Technology

  • Robotic Process Automation (RPA)
RPA can automate repetitive and time-consuming tasks with little added value (for example, faster data entry). It can reduce costs without changing the infrastructure.
  • Business process automation (often referred to as business process management or BPM)
And BPM is the automation of end-to-end business processes (for example, more accurate decision-making). BPM is usually the strategic foundation of an organization's digital transformation.

In general, low-code automation capabilities can more prompt companies that rely on repetitive processes to evaluate how to improve efficiency. They will need to retrain and redistribute employees to assume roles that can leverage their experience and institutional knowledge with strategic capabilities.

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Revitalizing OCR Using Innovative AI and Deep Learning Algorithms

Introduction

In this digital-oriented age, technology is advancing in such a way that it is paving the way for information extraction from handwritten documents or scanned images called Optical character recognition (OCR) data extraction. Thankfully, OCR technology has a wide range of applications to automate and enhance business operations. OCR technology allows data extraction from bank statements, product sheets, passports, contracts, receipts, invoices, utility bills, and a variety of other documents. 

In 2020, the global OCR market size hit the figure of USD 7.46 billion and it is expected that from 2021 to 2028, the market size will expand at a Compound Annual Growth Rate(CAGR) of 16.7%.  No doubt OCR technology performs accurate and reliable data extraction and plays a crucial role in financial infrastructures, insurance claim processing, legal and logistic documentation, but OCR systems cannot perform well with unstructured documents. IDP utilizes numerous AI technologies to pre-process, extract and post-process information to deal with these OCR shortcomings.  

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Artificial Intelligence and the Changing Cyber Security Landscape in 2021

There are many ways that artificial intelligence and machine learning can make a difference. Consider the situations below:

  • Self-driving cars will significantly reduce the number of road accidents and keep commuters safe. Google Maps suggesting an optimal commute to and from work and alerting about any congestion on your route. 
  • Email inboxes becoming smart enough to reply to emails on behalf of a person.
  • OCR software that deciphers handwritten cheques, enabling people to deposit cheques via a smartphone app. Or, a bank’s system detecting a transaction as possibly fraudulent and alerting the bank and the customer. What about investing platforms that provide financial advice to consumers by collating and learning from the best practices of investors and experts?
  • Social networking sites identifying friends and family in a photo and suggesting tagging them. Chat and instant messaging apps able to prompt textual or emoji responses to a received message.
  • Robotics Process Automation helping businesses increase productivity by automating everyday operations, handling exceptions, and resolving issues.
  • Asking a smart personal assistant, like Google, Alexa, Siri, or Cortana to search for something on the internet, or to set an alarm or reminder. Integrating Google and Alexa into homes, shopping online, ordering food, and calling and speaking with your friends and family at the convenience of sitting anywhere in the house and not holding a smartphone.
  • Amazon displays product recommendations to a shopper on the website or app even if the shopper did not specifically search for the product. Content and streaming platforms like Netflix, Amazon Prime, or Disney show a viewer what other content is popular based on something they watched in the past.

What’s Common in All the Situations Mentioned Above?

All of these have Artificial Intelligence (AI) and Machine Learning (ML) at play. It’s a wonder how technology has evolved, and the speed at which it has, that these accomplishments were made possible in the past decade. Application and adoption of AI increased exponentially during 2020 as the Covid-19 pandemic forced people, organizations, and governments to rethink everyday tasks.

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AI Will Be the Game Changer for IoT

Gartner expects that three trends will affect AI in the next few years. One, better communication (both ways) with people: Natural-language processing, generation, and contextual interpretation will make AI more comfortable to use and will improve the use of all computing resources.

Secondly, more in-depth and broader integration with existing applications and IoT projects: AI has its most significant value when built into architectures that drive business and service value.

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GPT-3 Does Not Understand What It Is Saying

Imagine that we sent a robot-controlled spaceship out to the far reaches of the galaxy to contact other life forms. On the ship, we placed a copy of all the text on the internet over the last three years so intelligent alien races would be able to learn something about us. After traveling twelve light-years, the ship enters the solar system around the star Luyten where it is boarded by aliens. The Luytenites retrieve the copy of the internet text and try to make sense of it.

They ask their top linguists to interpret these strange symbols but make little progress. The Luytenites were in the same position as eighteenth-century archaeologists who kept discovering stones with ancient Egyptian hieroglyphs. Finally, in 1799, archaeologists discovered the Rosetta stone which had both Egyptian hieroglyphs and ancient Greek text. Because they had what turned out to be the same decree in two languages, they were finally able to figure out the meanings of the hieroglyphs.

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Unrivaled Research and Development: How Technical SEO Can Change the R and D Game for Businesses

R&D is a heavily resource-rich aspect of business that can also consume more time and energy in overcoming the challenges that they sought to overcome. It can also form a creativity drain that may even fail to produce any tangible results. However, R&D is an essential innovative tool in the development of new technologies, products, and market insights. 

Meanwhile, SEO operates largely in the realm of marketing where R&D influenced technologies like machine learning and AI are beginning to enjoy heavier levels of influence. In an industry still dominated by the financial might of traditional companies, the influence of technology in SEO can help to provide smaller businesses and startups with a fighting chance. 

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Build a RingCentral Virtual Voicemail Assistant for Your Business   — Part 1

RingCentral Virtual Voicemail Assistant

Nowadays, consumers have a variety of options for obtaining services and getting the help they need. They can use webchat, email, the Internet, and face-to-face contact, yet telephone customer service is still the first choice for most customers when they have questions or a problem that needs to be resolved.

In order to ensure your customers are happy with the customer service they receive, it’s even more important for you to provide exceptional customer service, including outstanding telephone service. Consumers expect better service than ever before, and the capabilities of modern telephone communications allow you to offer them the satisfaction and resolution they demand.

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How Analytics and Data Science Improve Your Business Efficiency

Corporations, particularly those that are focused on making sales to a broad audience — as opposed to those selling a small number of large ticket items — have always had a keen interest in crunching numbers related to the ways customers interact with their brands to boost sales. This is what we might refer to as data analytics. But, many organizations opt to take their efforts a step further by using data science.

What Is Data Science and Analysis?

Techopedia defines data science as:

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The Vulnerability of IoT Cybersecurity

The use of IoT (Internet of Things) is rapidly growing; it is a never slow trend in today’s era. However, despite this exponential growth, cybersecurity is often the one thing being overlooked.  It is not wrong to say that the risks of a security breach are increasing with this growth. Future powerlessness and dependence on IoT can be improved by securing and responding to cybersecurity concerns.

Internet of Things (IoT)

The utilization of brilliantly associated gadgets and frameworks to use information accumulated by embedded sensors and actuators in machines and other physical items is called the Internet of Things (IoT). It is expected to rapidly spread in the coming years, and this union will release another measurement of administrations that enhance the quality of life of consumers and the efficiency of ventures, which will open doors for an opportunity that can be referred to as ‘connected life.'