The Datasaur Blog

News, updates, and insights from the Datasaur Team
Datasaur vs. Label Studio
May 14, 2022
Datasaur is a labeling platform that specializes in NLP. Within the first three years of the company’s growth, Datasaur has created audio, text, and OCR feature functions. Label Studio provides the ability to label audio, photos, text, HTML, and time series.
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The Subjective Nature of Data Labeling

In the space of NLP, labeling is a subjective experience. Every annotator will see each dataset a little bit differently. Managers of labeling projects have to create a system of review and clear instruction to ensure consistent, quality output.

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Datasaur vs. Label Studio

Datasaur is a labeling platform that specializes in NLP. Within the first three years of the company’s growth, Datasaur has created audio, text, and OCR feature functions. Label Studio provides the ability to label audio, photos, text, HTML, and time series.

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Data Labeling for Natural Language Processing: a Comprehensive Guide

ML is a “garbage in, garbage out” technology. The effectiveness of the resulting model is directly tied to the input data; data labeling is therefore a critical step in training ML algorithms. Indeed, increasing the quantity and quality of training data can be the most efficient way to improve an algorithm. And with ML’s growing popularity the labeling task is here to stay. As you approach setting up or revisiting your own labeling process, review the following guide.

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Datasaur vs. LabelBox

Labelbox and Datasaur both offer annotation software for organizations seeking to train their AI model. Although the two companies have many similarities, they do have some meaningful differences. Labelbox offers clients the ability to annotate images, text, audio, and video. Whereas Datasaur is focused on NLP data labeling, optimizing their platform for all things audio and text.

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What is Quantum Natural Language Processing?

There is a trend of big companies getting their hands dirty when it comes to Quantum Computing. These companies are working on quantum computing and have a mindset where they are to able reduce mistakes, increase accuracy and compute the data to use it practically. The conclusion the experts came to was in order for them to use a Quantum Computer, it must have a symbiotic relationship with a classical computer to create different outcomes.

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What is NLP and How is it Different from AI?

AI is a machine that uses subsets of technology like machine learning, deep learning, natural language processing to produce the optimum solution to the task provided. NLP helps bridge the gap between human interaction and machine understanding which improves the overall quality of AI. AI can hold simple and limited conversations like when one asks their google assistant a question, it uses the internet to answer. Though the answer is theoretically correct, it lacks a human touch. As NLP and AI progress, users will accumulate more trained data, eventually leading to a stage where the AI can handle a conversation without human interference.

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The Utility of AI in Corporate Law

AI can potentially transform how lawyers in legal departments work. Machine learning has already been heavily used for legal research and assists to predict litigation results. As mentioned above AI has been incorporated in many fields to increase productivity. AI takes care of tasks like drafting lower-exposure or lower-liability agreements like NDAs (Non-Disclosure Agreement).

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Using Artificial Intelligence for Breast Cancer Detection

The experts believe the AI-based triaging system could be used to immensely decrease the workload of the radiologists’. Verburg stated that this kind of approach will assist the radiologists to improve their overall reading time He also mentioned the fact that more time could become available for radiologists to focus on more complex breast MRI examinations. The experts involved, plan to train this deep learning model in other datasets and deploy it in the subsequent screening rounds of the DENSE trials.

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Using AI to Improve Hospital Discharge Papers

Artificial intelligence is a machine that is capable of performing tasks as a human would. Once AI hit the market it was integrated into almost all sectors of different industries. Of course, this also includes the medical field. Many tasks need to be performed daily. One of these tasks involves hospital discharge papers.

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How are Universities using AI?

AI has been transforming almost all aspects of different industries and sometimes is even more effective than humans while performing tasks. AI is simply the future and therefore it makes sense for universities to adopt the same as it will equip students to use the technology of their research. AI also helps in building a personalized and effective learning process for each student depending on their capability to cope with pressure and download content. This will assist the student to be fully prepared of their academic career.

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The Evolution of NLP

NLP is constantly evolving and impacting our world in a massive way. It started limited and rudimentary as rule-based methods. With an increase in data, it progressed to statistical learning which was used in simple question-answering, predictive text and more. NLP has been evolving and growing ever since, and now we are at a stage where we even fuse models to collaborate with each other. NLP is only getting better and improving its accuracy at a frightening speed. This is the future of the digital world.

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Social Media and Artificial Intelligence

Artificial intelligence assists social media platforms in controlling the pool of information and making sense of it to understand the brand new trends, user behavior, and their interests, find out and block abusive content, and for various other purposes. AI additionally plays a chief function in social media marketing by letting the brands measure the performance of the enterprise and pick out users that can be converted into potential customers.

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Summary of Guidance on Safe AI by the World Health Organization

WHO has developed principles to support efforts to ensure that the full potential of AI for healthcare and public health is achieved to benefit all. AI systems should be carefully designed according to the socio-economic and health-care settings of that region. AI training models must implement community engagement and awareness-raising for millions of healthcare workers who will require digital literacy.

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The Rise of AI in Robotics

AI-enabled robots are superior to non-AI machine, as these robots are capable of performing certain tasks while adapting to their environment. Therefore, AI-empowered robots are more intelligent than other machines. One can use training to make the computer understand physical and logistical data patterns. It can act according to its environment, robots are also integrated with various functions like computer vision, motion control, and grasping objects.

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The Rise of AI in the Pharmaceutical Industry

There are several practical applications of AI, such as disease identification and diagnosis, helping identify patients for clinical trials, drug manufacturing, and predictive forecasting to name a few. AI is so flexible that it can be inserted in every aspect of the pharmaceutical industry, starting from drug discovery and development to manufacturing and marketing. By inserting AI in the core workflows, pharma companies can make their operations efficient, cost-effective, and hassle-free.

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PyTorch vs. TensorFlow

If one compares the two frameworks, it entirely depends on your need, as switching from one to the other is also a seamless process. PyTorch seems to be a favorite among programmers and scientific researchers. The scientific community tends to prefer PyTorch while working on citations. Meanwhile, organizations and startups prefer TensorFlow. The reputed production features give TensorFlow a good case. Visualization with Tensorboard creates an attractive presentation for clients.

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New York City’s Ethical Pursuit of AI

As Artificial Intelligence becomes more popular, various beneficial implementations in different sectors come into mind. Artificial Intelligence is a computer that has capable of performing tasks mimicking a human efficiently. Inspired by all the positives AI brings up, New York City released a 116-page strategic vision for how it plans to benefit from artificial intelligence as a community but only does so ethically and responsibly.

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How does NLP work in Different Languages

There are many examples of NLP being applied practically, especially in systems like resume-parsing for hiring to Interactive Voice Response (IVR) systems. NLP is usually used for chatbots, virtual assistants, and modern spam detection. But NLP isn’t perfect, although there are over 7000 languages spoken around the globe, most NLP processes only use seven languages: English, Chinese, Urdu, Farsi, Arabic, French, and Spanish.

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NLP to the Rescue: Medical Applications

NLP in healthcare is becoming popular due to its potential to search, analyze and interpret stupendous amounts of patient datasets. Using advanced medical algorithms, machine learning in healthcare and NLP technology services have the potential to utilize suitable insights and concepts from the data buried in text form. NLP in healthcare media can accurately grant a voice to unstructured data of the healthcare Industry, giving spectacular insight into understanding quality, improving methods, and better results for patients.

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NLP: The Digital Warrior that Battles Misinformation

With so many sources of information NLP helps AI battle misinformation through tools like stance detection, Abstractive summarization, fact-checking, sentiment analysis, and many more. Each tool allows the AI to learn something about the source text, whether it understands the point of view, the emotion, or the stance behind it. This information ultimately helps the AI fact check and determine whether the information given is true or false.

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Using NLP for Automatic Speech Recognition

ASR with NLP is a topic trending to various kinds of research and innovations. Speech recognition is one of the main parts of this field. Many types of models and methods are available using existing technologies to recognize speech. Siri, Alex, and Google demonstrate what ASR and NLP have achieved thus far.

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The Impact of NLP on Online Retail Shopping

Natural Language Processing (NLP) is at the top of these adopted technologies. NLP has been headlined as one of the integral cogs of the online retail sphere. Putting into practice the uses of natural language processing and other AI-affinities technologies determines the difference between accomplishment and failure: AI in retail is a trend to watch out for!

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How is NLP Assisting in Keeping Real-Time Gaming Chats Safe?

Online platforms like social media, gaming chats, etc., connect the entire globe into one domain. In an environment that connects many users in one place, combatting abusive content should be the one number priority. This is where Natural Language Processing (NLP) comes to the rescue. NLP assists the AI in understanding ‘natural language’ of gamers in order to identify damaging/hurtful communication

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How NLP is being used to keep Youtube comments safe

NLP has a lot of tools to assist AI in understanding natural language. One of these tools is called Sentiment Analysis. Using sentiment analysis of comments, the user can understand their community acceptance of the channel/video. Organizations can also use it to analyze the trending videos, depending on their views, likes, comments, categories, etc. NLP combined with machine learning creates a safe comment space on YouTube.

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NLP Use Cases in the Insurance Industry

Insurance is a constantly evolving industry that has felt more pressure due to the pandemic. Integrating insurance systems with AI tech such as cloud computing, identity resolution, predictive analytics, and natural language processing equip insurers with powerful tools as they grapple with dramatically altered consumer needs, behaviors, and spending patterns. The insurance industry is walking towards a technology-filled future, and it's exciting to see.

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The Importance of Using NLP for Electronic Health and Medical Records

For the hand-written documents, we should scan the records to save them electronically. But the question is how does one use the “unstructured” and “non-standardized” in digital records? NLP (Natural Language Processing) techniques can seize unstructured information, examine the grammatical shape, decide the meaning of the data and summarize the information. As a result, NLP techniques can decrease expenses and extract ample data analytics information in-depth.

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NLP: The fuel for Chatbots

As chatbots are becoming more prevalent with companies, they are investing in technologies that will improve the chatbot they are working with. The necessary fundamentals that create a better functioning chatbot are essentially AI. NLP is absolutely essential in creating accurate and successful chatbots. There are a few standard NLP techniques that empower chatbots. This blog discusses the different NLP methods that help create a robust and comprehensive chatbot including, but not limited to OCR, NER, and more!

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How NLP has Revolutionized the Customer Care Experience

Several service sectors have implemented NLP, which has showcased its efficiency. The customer servicing sector always tends to have a massive load of work. By using NLP, companies have lessened the burden of customer care agents. Now agents can focus on more complex issues and leave the simple tedious work to AI.NLP uses many tools such as speech recognition, grammatical tagging, word sense disambiguation, named entity recognition, sentiment analysis, and many more to accurately interpret the intent behind a statement and improve the quality of the task at hand.

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NLP: A Potential Savior of the Covid-19 Outbreak

Recent studies have shown that NLP can beneficial for predicting Covid-19 outbreaks. Organizations are deploying NLP models to develop clinical voice assistants to transcribe patient visit information into their electronic health records (EHR) (An electronic health record contains a patient’s entire medical history). They deploy this technology to shorten the time a doctor spends on documentation: This creates more time for a clinician to work with patients directly during the pandemic.

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NATO’s Plan for AI

Since the adoption of the NATO AI Strategy, Allies are working towards cooperation and collaboration to meet these requirements in terms of both defense and security, NATO as the primary transatlantic forum. The goal of NATO’s AI Strategy is to speed up the process for AI adoption by amplifying key AI enablers and adapting policy, this includes adopting Principles of Responsible Use for AI. All these precautions are taken in order to avoid the malicious use of AI by state and non-state actors.

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Law and Order: NLP Edition

Natural Language Processing (NLP) is beginning to add "order" to the legal field. NLP has assisted the legal field in three distinct areas: contract review, electronic discovery, and general research. There is a massive demand for applying NLP in the legal system to help absorb a lot of information and streamline it: This allows humans to focus on more intricate tasks that AI cannot handle.

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Getting to know Automated Data Labeling

Data labeling simply means, the procedure of sleuthing and tagging information with labels, within a variety of pictures, videos, audio, and text assets. Data labeling usually uses human power to create tags and sometimes tags are created with the assistance of a computer. Data Labeling for machine learning (ML) teaches Artificial Intelligence (AI) to learn from the labeled data and eventually implement the knowledge it has gathered in real-time scenarios.

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Important Use Cases of NLP

NLP has many use cases. In this guide, we discuss some of those uses such as abstractive summary, text summarization, translation, autocorrect, and more. NLP has become an integral part of many industries. For example, in the medical industry used for dictation, clinical documentation, clinical trial matching, etc. NLP assists the AI to become a better functioning computer that behaves more efficiently than a human but simultaneously like a human.

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How is NLP Used to Conduct Sentiment Analysis

Sentiments analysis is a subset of Natural Language Processing (NLP). It is a data mining technique that measures and tries to understand people's opinions and stances through NLP. Computational linguistics and text analysis inspect information from the web, social media, and many other online sources. This data assesses people's emotions, sentiments, beliefs, or viewpoints, so it is also called opinion mining: essentially, companies utilize NLP to inspect people's moods in society.

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GPT-3: The Next Step of Advancement in AI

Generative Pre-trained Transformer 3 (GPT-3) has taken the technology sector by storm. It is the most talked-about AI, said to mimic writing like a human, also containing the largest neural network ever created to date. GPT-3 is the third version of artificial intelligence (AI) created by OpenAI. OpenAI is the research firm co-founded by Elon Musk for the advancement of AI. The third version has 175 billion parameters, which means that the values added, the neural network tries to optimize during training. By comparison, its predecessor GPT-2 already had 1.5 billion.

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Getting to know AI: Narrow vs. General

AI learns by devouring enormous amounts of data and deciphers the data for correlations and patterns. It uses these patterns to make predictions. For instance, chatbots are fed a blueprint of text chats that help them determine how humans interact with each other. Similarly, image recognition tools can learn to pinpoint and label objects in images by reviewing a surplus of data. AI focuses on 3 cognitive skills: learning, reasoning, and self-correction. AI can be broadly divided into 2 types: Narrow AI and General AI

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Fintech and NLP: Revolutionizing the Finance Sector

There are many promising explorations and late forward leaps into Natural Language Processing (NLP) and Artificial Intelligence (AI). What's more, these patterns are especially applicable in the finance sector. Over the years, text examination has become robotized and continually expanding exponentially. One could likewise work on human responsiveness.

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Everyone can be a Programmer: Using NLP to Create Applications

Natural language processing may also no longer sound like much. However, it is arguably a greater significant exchange to the man-machine interface than graphical user interfaces (GUI) were. At the convention, Microsoft’s concept was a no-code system whereby a user could interface with an NLP AI. Then the AI would automatically create the application the user needs. This effort could be achieved using a method that guaranteed the result was once impervious and complied with company insurance policies to keep away from growing issues whilst solving them.

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Differences Between AI, ML, and DL

Artificial Intelligence is made up of internal cogs like Machine Learning and Deep Learning. AI has become increasingly popular and has several real-world applications like Google’s AI-Powered Predictions, Ridesharing apps like Uber and Lyft, Commercial Flights Use an AI Autopilot, etc. For ML, there are a growing number of real-world applications that include Virtual Personal Assistants: Siri, Alexa, Google, etc., Email Spam, and Malware Filtering. Examples of DL applications include sentiment-based news aggregation, image analysis, and caption generation. Let's dig in.

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How do we Develop Ethical AI?

It is vital to continuously monitor the changes within the AI world because it is not feasible to supervise all of the outcomes. But growing a moral AI framework, bearing the best practices in mind, fostering the AI-bias-conscious lifestyle at your company, and monitoring the changes around moral AI could make the future safer. It is also crucial for any organization utilizing AI to have an accountability system: checks and balances: This is crucial to enjoying a fair and balanced AI of tomorrow.

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Datasaur acquires Konvergen AI

We’re thrilled to announce that Datasaur has acquired Konvergen AI, an industry-leading OCR technology startup from Indonesia. The two companies have collaborated on multiple projects throughout the years and Datasaur has integrated Konvergen AI’s tech for its notable capabilities in handwriting recognition, government ID field extraction, and intelligent document processing.

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Data Labeling and its Significance

ML is a “garbage in, garbage out” technology. The effectiveness of the resulting model is directly tied to the input data; data labeling is, therefore, a critical step in training ML algorithms. Indeed, increasing the quantity and quality of training data can be the most efficient way to improve an algorithm. And with ML’s growing popularity the labeling task is here to stay.

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Can AI Benefit your Company’s Recruiting Efforts?

Recruitment requires building connections and AI can provide assistance easily for the same. The AI streamlines and automates most transactional parts of recruitment, which allows the recruiters not only to work more efficiently but allows them to build relationships with candidates, which ultimately leads to better business performance.

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How do Banks use AI?

AI-powered systems have a common knowledge in today’s day and age, especially after Covid. AI brings the opportunity to more efficiently and address the workload of agents by segregating and making sense of the data. With the power of AI in banks, one can expect: An improved customer experience, Saves time both for the customer as well as for the bank, reduces human error, Builds a strong and loyal customer, Deals with cashless transactions from any place and at any time.

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Audio Launch 🔊

Datasaur's Audio Annotation Tool will allow you to improve the quality of your audio transcription with our easy-to-use interface. Modify timestamps and transcription with minimal clicks. Classify audio by identifying speakers, sound type, or topics. Play your audio and follow along in the transcription automatically. If this sounds appealing to you and your team, join our waitlist today and reach out to demo@datasaur.ai. We're just getting started and we're excited to see the audio AI you'll be building out using our platform.

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Using AI to Discover the Mysteries of the Human Genome

AI has a plethora of potential within genomics and may facilitate drug target identification and the development of capacity new therapeutics. The genome is an incredibly complex and mysterious entity. It wraps itself in a beautifully complex code and language. The information it contains is seemingly infinite across the span of our planet's species. However, maybe by the stroke of AI--we may begin to unravel some of that beautiful mystery.

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The Development of AI in Psychiatry

AI has become a kind of hub for digital interventions, gravitating towards smartphones and mobile applications, to magnify user experience and refine personalized mental health care. If one takes the prediction and detection model into consideration, an abundance of datasets dictates that data-driven AI methods can be deployed to develop prediction/detection models for mental health conditions.

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AI in Content Marketing

AI is good for time-consuming tasks that do not require creativity. However, even while giving tasks to AI, it cannot function a hundred percent without human intervention. As AI evolves, it would be introduced to a high level of complexity in training. Therefore, people are needed, but they must be ready for the wave of change that is looming over them and get ready to take on different complex roles in their respective companies.

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A Compliance Solution: NLP

Natural Language Processing (NLP) is an off-shoot of Artificial Intelligence (AI) that assists AI to understand human language (Natural language). Human or natural language means the way humans interact with each other.

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NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

NLP: the Fuel for Chatbots

Nartural Language Processing (NLP_ is beginning to add “order” to the legal field. Read this article to get  an understanding of all the ways in which NLP can save massive amounts of time and energy for legal firms and organizations.

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NLP Use Cases in the Insurance Industry

Insurance is a constantly evolving industry that has felt more pressure due to the pandemic. Integrating insurance systems with AI tech such as cloud computing, identity resolution, predictive analytics, and natural language processing equip insurers with powerful tools as they grapple with dramatically altered consumer needs, behaviors, and spending patterns. The insurance industry is walking towards a technology-filled future, and it's exciting to see.

No items found.
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Differences Between AI, ML, and DL

Artificial Intelligence is made up of internal cogs like Machine Learning and Deep Learning. AI has become increasingly popular and has several real-world applications like Google’s AI-Powered Predictions, Ridesharing apps like Uber and Lyft, Commercial Flights Use an AI Autopilot, etc. For ML, there are a growing number of real-world applications that include Virtual Personal Assistants: Siri, Alexa, Google, etc., Email Spam, and Malware Filtering. Examples of DL applications include sentiment-based news aggregation, image analysis, and caption generation. Let's dig in.

No items found.
Post Image
Important Use Cases of NLP

NLP has many use cases. In this guide, we discuss some of those uses such as abstractive summary, text summarization, translation, autocorrect, and more. NLP has become an integral part of many industries. For example, in the medical industry used for dictation, clinical documentation, clinical trial matching, etc. NLP assists the AI to become a better functioning computer that behaves more efficiently than a human but simultaneously like a human.

No items found.
Post Image
The Evolution of NLP

NLP is constantly evolving and impacting our world in a massive way. It started limited and rudimentary as rule-based methods. With an increase in data, it progressed to statistical learning which was used in simple question-answering, predictive text and more. NLP has been evolving and growing ever since, and now we are at a stage where we even fuse models to collaborate with each other. NLP is only getting better and improving its accuracy at a frightening speed. This is the future of the digital world.

No items found.
Post Image
What is NLP and How is it Different from AI?

AI is a machine that uses subsets of technology like machine learning, deep learning, natural language processing to produce the optimum solution to the task provided. NLP helps bridge the gap between human interaction and machine understanding which improves the overall quality of AI. AI can hold simple and limited conversations like when one asks their google assistant a question, it uses the internet to answer. Though the answer is theoretically correct, it lacks a human touch. As NLP and AI progress, users will accumulate more trained data, eventually leading to a stage where the AI can handle a conversation without human interference.

No items found.
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The Subjective Nature of Data Labeling

In the space of NLP, labeling is a subjective experience. Every annotator will see each dataset a little bit differently. Managers of labeling projects have to create a system of review and clear instruction to ensure consistent, quality output.

NLP
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Datasaur vs. Label Studio

Datasaur is a labeling platform that specializes in NLP. Within the first three years of the company’s growth, Datasaur has created audio, text, and OCR feature functions. Label Studio provides the ability to label audio, photos, text, HTML, and time series.

Company
Post Image
Datasaur vs. LabelBox

Labelbox and Datasaur both offer annotation software for organizations seeking to train their AI model. Although the two companies have many similarities, they do have some meaningful differences. Labelbox offers clients the ability to annotate images, text, audio, and video. Whereas Datasaur is focused on NLP data labeling, optimizing their platform for all things audio and text.

Company
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Data Labeling for Natural Language Processing: a Comprehensive Guide

ML is a “garbage in, garbage out” technology. The effectiveness of the resulting model is directly tied to the input data; data labeling is therefore a critical step in training ML algorithms. Indeed, increasing the quantity and quality of training data can be the most efficient way to improve an algorithm. And with ML’s growing popularity the labeling task is here to stay. As you approach setting up or revisiting your own labeling process, review the following guide.

NLP
Post Image
A Compliance Solution: NLP

Natural Language Processing (NLP) is an off-shoot of Artificial Intelligence (AI) that assists AI to understand human language (Natural language). Human or natural language means the way humans interact with each other.

No items found.
Post Image
AI in Content Marketing

AI is good for time-consuming tasks that do not require creativity. However, even while giving tasks to AI, it cannot function a hundred percent without human intervention. As AI evolves, it would be introduced to a high level of complexity in training. Therefore, people are needed, but they must be ready for the wave of change that is looming over them and get ready to take on different complex roles in their respective companies.

No items found.
Post Image
The Development of AI in Psychiatry

AI has become a kind of hub for digital interventions, gravitating towards smartphones and mobile applications, to magnify user experience and refine personalized mental health care. If one takes the prediction and detection model into consideration, an abundance of datasets dictates that data-driven AI methods can be deployed to develop prediction/detection models for mental health conditions.

No items found.
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Using AI to Discover the Mysteries of the Human Genome

AI has a plethora of potential within genomics and may facilitate drug target identification and the development of capacity new therapeutics. The genome is an incredibly complex and mysterious entity. It wraps itself in a beautifully complex code and language. The information it contains is seemingly infinite across the span of our planet's species. However, maybe by the stroke of AI--we may begin to unravel some of that beautiful mystery.

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Audio Launch 🔊

Datasaur's Audio Annotation Tool will allow you to improve the quality of your audio transcription with our easy-to-use interface. Modify timestamps and transcription with minimal clicks. Classify audio by identifying speakers, sound type, or topics. Play your audio and follow along in the transcription automatically. If this sounds appealing to you and your team, join our waitlist today and reach out to demo@datasaur.ai. We're just getting started and we're excited to see the audio AI you'll be building out using our platform.

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How do Banks use AI?

AI-powered systems have a common knowledge in today’s day and age, especially after Covid. AI brings the opportunity to more efficiently and address the workload of agents by segregating and making sense of the data. With the power of AI in banks, one can expect: An improved customer experience, Saves time both for the customer as well as for the bank, reduces human error, Builds a strong and loyal customer, Deals with cashless transactions from any place and at any time.

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Can AI Benefit your Company’s Recruiting Efforts?

Recruitment requires building connections and AI can provide assistance easily for the same. The AI streamlines and automates most transactional parts of recruitment, which allows the recruiters not only to work more efficiently but allows them to build relationships with candidates, which ultimately leads to better business performance.

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Data Labeling and its Significance

ML is a “garbage in, garbage out” technology. The effectiveness of the resulting model is directly tied to the input data; data labeling is, therefore, a critical step in training ML algorithms. Indeed, increasing the quantity and quality of training data can be the most efficient way to improve an algorithm. And with ML’s growing popularity the labeling task is here to stay.

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Datasaur acquires Konvergen AI

We’re thrilled to announce that Datasaur has acquired Konvergen AI, an industry-leading OCR technology startup from Indonesia. The two companies have collaborated on multiple projects throughout the years and Datasaur has integrated Konvergen AI’s tech for its notable capabilities in handwriting recognition, government ID field extraction, and intelligent document processing.

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How do we Develop Ethical AI?

It is vital to continuously monitor the changes within the AI world because it is not feasible to supervise all of the outcomes. But growing a moral AI framework, bearing the best practices in mind, fostering the AI-bias-conscious lifestyle at your company, and monitoring the changes around moral AI could make the future safer. It is also crucial for any organization utilizing AI to have an accountability system: checks and balances: This is crucial to enjoying a fair and balanced AI of tomorrow.

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Everyone can be a Programmer: Using NLP to Create Applications

Natural language processing may also no longer sound like much. However, it is arguably a greater significant exchange to the man-machine interface than graphical user interfaces (GUI) were. At the convention, Microsoft’s concept was a no-code system whereby a user could interface with an NLP AI. Then the AI would automatically create the application the user needs. This effort could be achieved using a method that guaranteed the result was once impervious and complied with company insurance policies to keep away from growing issues whilst solving them.

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Fintech and NLP: Revolutionizing the Finance Sector

There are many promising explorations and late forward leaps into Natural Language Processing (NLP) and Artificial Intelligence (AI). What's more, these patterns are especially applicable in the finance sector. Over the years, text examination has become robotized and continually expanding exponentially. One could likewise work on human responsiveness.

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Getting to know AI: Narrow vs. General

AI learns by devouring enormous amounts of data and deciphers the data for correlations and patterns. It uses these patterns to make predictions. For instance, chatbots are fed a blueprint of text chats that help them determine how humans interact with each other. Similarly, image recognition tools can learn to pinpoint and label objects in images by reviewing a surplus of data. AI focuses on 3 cognitive skills: learning, reasoning, and self-correction. AI can be broadly divided into 2 types: Narrow AI and General AI

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GPT-3: The Next Step of Advancement in AI

Generative Pre-trained Transformer 3 (GPT-3) has taken the technology sector by storm. It is the most talked-about AI, said to mimic writing like a human, also containing the largest neural network ever created to date. GPT-3 is the third version of artificial intelligence (AI) created by OpenAI. OpenAI is the research firm co-founded by Elon Musk for the advancement of AI. The third version has 175 billion parameters, which means that the values added, the neural network tries to optimize during training. By comparison, its predecessor GPT-2 already had 1.5 billion.

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How is NLP Used to Conduct Sentiment Analysis

Sentiments analysis is a subset of Natural Language Processing (NLP). It is a data mining technique that measures and tries to understand people's opinions and stances through NLP. Computational linguistics and text analysis inspect information from the web, social media, and many other online sources. This data assesses people's emotions, sentiments, beliefs, or viewpoints, so it is also called opinion mining: essentially, companies utilize NLP to inspect people's moods in society.

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Getting to know Automated Data Labeling

Data labeling simply means, the procedure of sleuthing and tagging information with labels, within a variety of pictures, videos, audio, and text assets. Data labeling usually uses human power to create tags and sometimes tags are created with the assistance of a computer. Data Labeling for machine learning (ML) teaches Artificial Intelligence (AI) to learn from the labeled data and eventually implement the knowledge it has gathered in real-time scenarios.

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Law and Order: NLP Edition

Natural Language Processing (NLP) is beginning to add "order" to the legal field. NLP has assisted the legal field in three distinct areas: contract review, electronic discovery, and general research. There is a massive demand for applying NLP in the legal system to help absorb a lot of information and streamline it: This allows humans to focus on more intricate tasks that AI cannot handle.

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NATO’s Plan for AI

Since the adoption of the NATO AI Strategy, Allies are working towards cooperation and collaboration to meet these requirements in terms of both defense and security, NATO as the primary transatlantic forum. The goal of NATO’s AI Strategy is to speed up the process for AI adoption by amplifying key AI enablers and adapting policy, this includes adopting Principles of Responsible Use for AI. All these precautions are taken in order to avoid the malicious use of AI by state and non-state actors.

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NLP: A Potential Savior of the Covid-19 Outbreak

Recent studies have shown that NLP can beneficial for predicting Covid-19 outbreaks. Organizations are deploying NLP models to develop clinical voice assistants to transcribe patient visit information into their electronic health records (EHR) (An electronic health record contains a patient’s entire medical history). They deploy this technology to shorten the time a doctor spends on documentation: This creates more time for a clinician to work with patients directly during the pandemic.

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How NLP has Revolutionized the Customer Care Experience

Several service sectors have implemented NLP, which has showcased its efficiency. The customer servicing sector always tends to have a massive load of work. By using NLP, companies have lessened the burden of customer care agents. Now agents can focus on more complex issues and leave the simple tedious work to AI.NLP uses many tools such as speech recognition, grammatical tagging, word sense disambiguation, named entity recognition, sentiment analysis, and many more to accurately interpret the intent behind a statement and improve the quality of the task at hand.

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NLP: The fuel for Chatbots

As chatbots are becoming more prevalent with companies, they are investing in technologies that will improve the chatbot they are working with. The necessary fundamentals that create a better functioning chatbot are essentially AI. NLP is absolutely essential in creating accurate and successful chatbots. There are a few standard NLP techniques that empower chatbots. This blog discusses the different NLP methods that help create a robust and comprehensive chatbot including, but not limited to OCR, NER, and more!

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The Importance of Using NLP for Electronic Health and Medical Records

For the hand-written documents, we should scan the records to save them electronically. But the question is how does one use the “unstructured” and “non-standardized” in digital records? NLP (Natural Language Processing) techniques can seize unstructured information, examine the grammatical shape, decide the meaning of the data and summarize the information. As a result, NLP techniques can decrease expenses and extract ample data analytics information in-depth.

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How NLP is being used to keep Youtube comments safe

NLP has a lot of tools to assist AI in understanding natural language. One of these tools is called Sentiment Analysis. Using sentiment analysis of comments, the user can understand their community acceptance of the channel/video. Organizations can also use it to analyze the trending videos, depending on their views, likes, comments, categories, etc. NLP combined with machine learning creates a safe comment space on YouTube.

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How is NLP Assisting in Keeping Real-Time Gaming Chats Safe?

Online platforms like social media, gaming chats, etc., connect the entire globe into one domain. In an environment that connects many users in one place, combatting abusive content should be the one number priority. This is where Natural Language Processing (NLP) comes to the rescue. NLP assists the AI in understanding ‘natural language’ of gamers in order to identify damaging/hurtful communication

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The Impact of NLP on Online Retail Shopping

Natural Language Processing (NLP) is at the top of these adopted technologies. NLP has been headlined as one of the integral cogs of the online retail sphere. Putting into practice the uses of natural language processing and other AI-affinities technologies determines the difference between accomplishment and failure: AI in retail is a trend to watch out for!

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Using NLP for Automatic Speech Recognition

ASR with NLP is a topic trending to various kinds of research and innovations. Speech recognition is one of the main parts of this field. Many types of models and methods are available using existing technologies to recognize speech. Siri, Alex, and Google demonstrate what ASR and NLP have achieved thus far.

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NLP: The Digital Warrior that Battles Misinformation

With so many sources of information NLP helps AI battle misinformation through tools like stance detection, Abstractive summarization, fact-checking, sentiment analysis, and many more. Each tool allows the AI to learn something about the source text, whether it understands the point of view, the emotion, or the stance behind it. This information ultimately helps the AI fact check and determine whether the information given is true or false.

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NLP to the Rescue: Medical Applications

NLP in healthcare is becoming popular due to its potential to search, analyze and interpret stupendous amounts of patient datasets. Using advanced medical algorithms, machine learning in healthcare and NLP technology services have the potential to utilize suitable insights and concepts from the data buried in text form. NLP in healthcare media can accurately grant a voice to unstructured data of the healthcare Industry, giving spectacular insight into understanding quality, improving methods, and better results for patients.

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How does NLP work in Different Languages

There are many examples of NLP being applied practically, especially in systems like resume-parsing for hiring to Interactive Voice Response (IVR) systems. NLP is usually used for chatbots, virtual assistants, and modern spam detection. But NLP isn’t perfect, although there are over 7000 languages spoken around the globe, most NLP processes only use seven languages: English, Chinese, Urdu, Farsi, Arabic, French, and Spanish.

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New York City’s Ethical Pursuit of AI

As Artificial Intelligence becomes more popular, various beneficial implementations in different sectors come into mind. Artificial Intelligence is a computer that has capable of performing tasks mimicking a human efficiently. Inspired by all the positives AI brings up, New York City released a 116-page strategic vision for how it plans to benefit from artificial intelligence as a community but only does so ethically and responsibly.

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PyTorch vs. TensorFlow

If one compares the two frameworks, it entirely depends on your need, as switching from one to the other is also a seamless process. PyTorch seems to be a favorite among programmers and scientific researchers. The scientific community tends to prefer PyTorch while working on citations. Meanwhile, organizations and startups prefer TensorFlow. The reputed production features give TensorFlow a good case. Visualization with Tensorboard creates an attractive presentation for clients.

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The Rise of AI in the Pharmaceutical Industry

There are several practical applications of AI, such as disease identification and diagnosis, helping identify patients for clinical trials, drug manufacturing, and predictive forecasting to name a few. AI is so flexible that it can be inserted in every aspect of the pharmaceutical industry, starting from drug discovery and development to manufacturing and marketing. By inserting AI in the core workflows, pharma companies can make their operations efficient, cost-effective, and hassle-free.

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The Rise of AI in Robotics

AI-enabled robots are superior to non-AI machine, as these robots are capable of performing certain tasks while adapting to their environment. Therefore, AI-empowered robots are more intelligent than other machines. One can use training to make the computer understand physical and logistical data patterns. It can act according to its environment, robots are also integrated with various functions like computer vision, motion control, and grasping objects.

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Summary of Guidance on Safe AI by the World Health Organization

WHO has developed principles to support efforts to ensure that the full potential of AI for healthcare and public health is achieved to benefit all. AI systems should be carefully designed according to the socio-economic and health-care settings of that region. AI training models must implement community engagement and awareness-raising for millions of healthcare workers who will require digital literacy.

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Social Media and Artificial Intelligence

Artificial intelligence assists social media platforms in controlling the pool of information and making sense of it to understand the brand new trends, user behavior, and their interests, find out and block abusive content, and for various other purposes. AI additionally plays a chief function in social media marketing by letting the brands measure the performance of the enterprise and pick out users that can be converted into potential customers.

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How are Universities using AI?

AI has been transforming almost all aspects of different industries and sometimes is even more effective than humans while performing tasks. AI is simply the future and therefore it makes sense for universities to adopt the same as it will equip students to use the technology of their research. AI also helps in building a personalized and effective learning process for each student depending on their capability to cope with pressure and download content. This will assist the student to be fully prepared of their academic career.

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Using AI to Improve Hospital Discharge Papers

Artificial intelligence is a machine that is capable of performing tasks as a human would. Once AI hit the market it was integrated into almost all sectors of different industries. Of course, this also includes the medical field. Many tasks need to be performed daily. One of these tasks involves hospital discharge papers.

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Using Artificial Intelligence for Breast Cancer Detection

The experts believe the AI-based triaging system could be used to immensely decrease the workload of the radiologists’. Verburg stated that this kind of approach will assist the radiologists to improve their overall reading time He also mentioned the fact that more time could become available for radiologists to focus on more complex breast MRI examinations. The experts involved, plan to train this deep learning model in other datasets and deploy it in the subsequent screening rounds of the DENSE trials.

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The Utility of AI in Corporate Law

AI can potentially transform how lawyers in legal departments work. Machine learning has already been heavily used for legal research and assists to predict litigation results. As mentioned above AI has been incorporated in many fields to increase productivity. AI takes care of tasks like drafting lower-exposure or lower-liability agreements like NDAs (Non-Disclosure Agreement).

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What is Quantum Natural Language Processing?

There is a trend of big companies getting their hands dirty when it comes to Quantum Computing. These companies are working on quantum computing and have a mindset where they are to able reduce mistakes, increase accuracy and compute the data to use it practically. The conclusion the experts came to was in order for them to use a Quantum Computer, it must have a symbiotic relationship with a classical computer to create different outcomes.

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"Most comprehensive labelling tool in the market. Datasaur has saved us countless hours in building our own solution. My team lead never wants to go back to spreadsheets!"

G2 Reviewer

"Operating in an industry where we have to be privacy- and security-conscientious with our data, Datasaur was the only acceptable solution for us. We recommend them for both feature set and support responsiveness."

G2 Reviewer

"...information labeling tasks has been reduced by 80% which has allowed us to optimize our workflow much more, allowing us to focus on other areas that are also priorities for us..."

Mary L