The Next 10 Years Look Golden for Natural Language Processing Research
Stock Market Prediction With Natural Language Machine Learning
Machines – is there anything they can't learn? 20 years ago, the answer to that question would be very different. However, with modern processing power and deep learning tools, it seems that computers are getting quite nifty in the brainpower department. In that vein, a research group attempted to use machine learning tools to predict stock market performance, based on publicly available earnings documents.
The team used the Azure Machine Learning Workbench to build their model, one of many tools now out in the marketplace for such work. To train their model, earnings releases were combined with stock price data before and after the announcements were made. Natural language processing was used to interpret the earnings releases, with steps taken to purify the input by removing stop words, punctuation, and other ephemera. The model then attempted to find a relationship between the language content of the releases and the following impact on the stock price.
Particularly interesting were the vocabulary issues the team faced throughout the development process. In many industries, there is a significant amount of jargon – that is, vocabulary that is highly specific to the topic in question. The team decided to work around this, by comparing stocks on an industry-by-industry basis. There's little reason to be looking at phrases like "blood pressure medication" and "kidney stones" when you're comparing stocks in the defence electronics industry, after all.
With a model built, the team put it to the test. Stocks were sorted into 3 bins — low performing, middle performing, and high performing. Their most successful result was a 62% chance of predicting a low performing stock, well above the threshold for chance. This suggests that there's plenty of scope for further improvement in this area. As with anything in the stock market space, expect development in this area to continue at a furious pace.
We've seen machine learning do great things before, too – even creative tasks, like naming tomatoes.
Deep Learning For Natural Language Processing
Deep Learning is becoming increasingly important in a technology-dominated world. However, the building of computational models that accurately represent linguistic structures is complex, as it involves an in-depth knowledge of neural networks, and the understanding of advanced mathematical concepts such as calculus and statistics. This book makes these complexities accessible to those from a humanities and social sciences background, by providing a clear introduction to deep learning for natural language processing. It covers both theoretical and practical aspects, and assumes minimal knowledge of machine learning, explaining the theory behind natural language in an easy-to-read way. It includes pseudo code for the simpler algorithms discussed, and actual Python code for the more complicated architectures, using modern deep learning libraries such as PyTorch and Hugging Face. Providing the necessary theoretical foundation and practical tools, this book will enable readers to immediately begin building real-world, practical natural language processing systems.
What Companies Are Fueling The Progress In Natural Language Processing? Moving This Branch Of AI Past Translators And Speech-To-Text
AFP via Getty Images Key takeawaysChatbots have exploded in popularity in recent months, and there's a growing buzz surrounding the field of artificial intelligence and its various subsets. Natural language processing (NLP) is the subset of artificial intelligence (AI) that uses machine learning technology to allow computers to comprehend human language.
AI has many applications, including everything from self-driving cars to AI-driven investing. If you're curious about what AI can do for your portfolio, download the Q.Ai app to get started.
Natural language processing applications have moved beyond basic translators and speech-to-text with the emergence of ChatGPT and other powerful tools. We will look at this branch of AI and the companies fueling the recent progress in this area.
What's natural language processing all about?Natural language processing (NLP) is a subset of artificial intelligence (AI) that uses linguistics, machine learning, deep learning and coding to make human language comprehensible for machines. Natural language processing is a computer process enabling machines to understand and respond to text or voice inputs. The goal is for the machine to respond with text or voice as a human would.
The long-term objective of NLP is to help computers understand sentiment and intent so that we can move beyond basic language translators. This subset of AI focuses on interactive voice responses, text analytics, speech analytics and pattern and image recognition. One of the most popular uses right now is the text analytics segment since companies globally use this to improve customer service by analyzing consumer inputs.
The potential for NLP is formidable. According to Fortune Business Insights, the global market size for natural language processing could reach $161.81 billion by 2029. Market research conducted by IBM in 2021 showed that about half of businesses were utilizing NLP applications, many of which were in customer service.
How are businesses using NLP to improve operations?The primary benefit of NLP solutions for businesses is to use automation to cut costs and improve business operations to maximize productivity and profitability. Here are a few ways that NLP is being utilized right now by businesses globally:
You may be using NLP services daily without even noticing it. We enjoy more and more of these technological benefits as they advance. Here are some common examples of NLP:
We also can't ignore the role of AI and NLP in everyday services like streaming platforms and e-commerce websites (Amazon), where it feels like our results are customized by someone who knows us.
What companies are fueling the progress in natural language processing?While almost every business has to use some form of NLP and AI in its operations, some companies are fueling the recent progress in these technologies. Here are five companies in this space to keep an eye on.
MicrosoftMicrosoft has been making headlines lately since the company reportedly invested $10 billion in OpenAI, the startup behind DALL-E 2 and ChatGPT. These two tools alone have changed the entire landscape of AI and NLP innovations as the improvements bring this technology to the general public in new, exciting ways.
Microsoft Azure is the exclusive cloud provider for ChatGPT, and this platform also offers many services related to NLP. Some services include sentiment analysis, text classification, text summarization and entailment services.
IBMWhile IBM has generally been at the forefront of AI advancements, the company also offers specific NLP services. IBM allows you to build applications and solutions that use NLP to improve business operations.
One of the revenue streams for the company is the IBM Watson Natural Language Understanding service which uses deep learning to derive meaning from unstructured text data. On the Watson website, IBM touts that users have seen a 383% ROI over three years and that companies can increase productivity by 50% by reducing their time on information-gathering tasks.
AmazonThe significance of AI and NLP is felt at almost every level of Amazon's business. You may have used the Alexa device to put on your favorite song or found the perfect product on the e-commerce platform based on a recommendation. These are AI and NLP in action.
Amazon also offers Amazon Web Services (AWS) for cloud storage so businesses can complete their digital transformations. They also have Amazon Comprehend, an NLP service that uses machine learning to determine text's significance. The Comprehend service also offers sentiment analysis and custom segmentation so customers can add NLP to their apps.
LemonadeWhen discussing AI, you can't forget about the first insurance company fully Google
Even though Alphabet, the parent company of Google, recently revealed that it would be cutting 12,000 employees worldwide, they're also planning on launching 20 new products. Google has already offered a small sample group an exclusive look at a tool that will eventually be a competitor to ChatGPT, known as Bard. This chatbot is
The biggest issue for Google is that they want to offer an AI-powered chatbot that's safe, tackles misinformation, and shares factually accurate information. Google has been investing heavily in AI, and it's no secret that management wants to bring the company back to the forefront of this field. You can see Google utilizing NLP technology in every aspect of its business, including spam filters, predictive text when writing emails, search engines and translation tools.
How can you invest in NLP and AI?If you're a proponent of machine learning, there are many different ways to invest in AI and related technologies. There aren't companies that only focus on AI in the same way that Tesla focuses on EVs or Nike focuses on athletic wear because every successful business relies on some form of AI. You can, however, invest in major tech companies since they're becoming increasingly invested in AI. With Amazon relying on AI on everything from the Alexa device to powering the warehouses, this is one company that's all in.
OpenAI is projected to generate $1 billion in revenue in 2024. While you can't invest directly in OpenAI since they're a startup, you can invest in Microsoft or Nvidia. Microsoft's Azure will be the exclusive cloud provider for the startup, and most AI-based tools will rely on Nvidia for processing capabilities. In recent weeks, shares of Nvidia have shot up as the stock has been a favorite of investors looking to capitalize on this field.
You don't have to look any further if you want to see the capabilities of AI in investing. Q.Ai uses AI to offer investment options for those who don't want to be tracking the stock market daily. The good news is that Q.Ai also takes the guesswork out of investing if you want a hands-off approach. Check out the Emerging Tech Kit if you're a proponent of innovative technology.
The bottom lineNatural language processing and artificial intelligence are changing how businesses operate and impacting our daily lives. Significant advancements will continue with NLP using computational linguistics and machine learning to help machines process human language. As businesses worldwide continue to take advantage of NLP technology, the expectation is that they will improve productivity and profitability.
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