AtScale Unveils Breakthrough in Natural Language Processing with Semantic Layer and Generative AI

At a recent conference at MIT experts forecasted that it will affect all areas of industry from advertising and market research to consumer products. EWeek has the latest technology news and analysis, buying guides, and product reviews for IT professionals and technology buyers. The site’s focus is on innovative solutions and covering in-depth technical content. EWeek stays on the cutting edge of technology news and IT trends through interviews and expert analysis. Gain insight from top innovators and thought leaders in the fields of IT, business, enterprise software, startups, and more.

Sponsored Partner Content

• The resulting algorithms had become far more accurate and utilitarian.
• Fluree was selected by Lead Semantics because it is the only permissioned trust based ledger database that has semantic underpinnings for integration to enable connected data insights and standard semantic querying.
• Semantic Reactor to some extent complements Google’s AutoML Natural Language, an extension of its Cloud AutoML machine learning platform to the natural language processing domain.

A head shake can mean agree, disagree, confused, or simply a stiff neck. Sentiment thus plays a very important role in decision making and the ability of a machine to convert human language into machine readable code and convert it into actionable insights is the capability offered by NLP. In our previous research, we have largely focused on the quantitative methods of analysis. While quantitative data is easier to compartmentalize in the form of, say, share prices, time-series data analysis, qualitative data is harder to define and statistically model. NLP will also lead to more advanced analysis of medical data.

It’s also often necessary to refine natural language processing systems for specific tasks, such as a chatbot or a smart speaker. But even after this takes place, a natural language processing system may not always work as billed. They can encounter problems when people misspell or mispronounce words and they sometimes misunderstand intent and translate phrases incorrectly.

AI That Knows Your Business: Meet Cube D3

NLP has the ability to parse through unstructured data—social media analysis is a prime example—extract common word and phrasing patterns and transform this data into a guidepost for how social media and online conversations are trending. This capability is also valuable for understanding product reviews, the effectiveness of advertising campaigns, how people are reacting to news and other events, and various other purposes. Sentiment analysis finds things that might otherwise evade human detection. Semantic Reactor to some extent complements Google’s AutoML Natural Language, an extension of its Cloud AutoML machine learning platform to the natural language processing domain. That service launched publicly last December, and it supports for tasks like classification, sentiment analysis, and entity extraction, as well as a range of file formats including native and scanned PDFs.

Datadog President Amit Agarwal on Trends in…

The tech giant describes it as a demonstration of how natural language understanding (NLU) can be used with pretrained, generic AI models, as well as a means to dispel intimidation around using machine learning. Fluree was selected by Lead Semantics because it is the only permissioned trust based ledger database that has semantic underpinnings for integration to enable connected data insights and standard semantic querying. TextDistil, through its automated knowledge extraction, extends high fidelity tracing back to the source natural language text to provide governing context and auspices to the transactions that are recorded in the Fluree Ledger database.

Unlocking Unstructured Data with GenAI No Comments

We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI. Join leaders from Block, GSK, and SAP for an exclusive look at how autonomous agents are reshaping enterprise workflows – from real-time decision-making to end-to-end automation. Explore the future of AI on August 5 in San Francisco—join Block, GSK, and SAP at Autonomous Workforces to discover how enterprises are scaling multi-agent systems with real-world results. You can download the full report here, which includes detailed statistics, charts, and a deeper dive into the analysis.

These systems can also connect a customer to a live agent, when necessary. Voice systems allow customers to verbally say what they need rather than push buttons on the phone. While LLMs excel at generating human-like text, they often struggle with complex database schemas and business logic. AtScale’s Semantic Layer bridges this gap by providing LLMs with comprehensive business-side metadata, eliminating the need to create metrics from scratch or generate complex joins, and significantly enhancing result consistency and accuracy. Recent advances in each of these sub-topics has allowed us to use NLP to a deeper understanding of public perception of products, services, brands and companies.

This thereby seamlessly enhances the automated audit trail to mitigate risk while improving data provenance. A key area of focus for the integrated solution includes highly regulated industries, with a greater magnitude and scope of requirements needed to prove compliance, including fintech, banking, insurance and the public sector, among others. Today, prominent natural language models are available under licensing models. These include the OpenAI codex, LaMDA by Google, IBM Watson and software development tools such as CodeWhisperer and CoPilot.

Get the Free Newsletter!

As enterprises generate and store increasing volumes of data, the demand for quick, accurate data analysis has never been higher, outpacing traditional methods reliant on human analysts. AtScale’s integration of Generative AI transforms natural language queries into precise SQL commands, dramatically improving efficiency and decision-making speed. TextDistil addresses the current market interest in text and knowledge graphs — turning text into data that provides context to support immutable transactions. Fluree brings trust and security to that data, which mitigates risk and extends data governance into unstructured enterprise information.

The OpenAI codex can generate entire documents, based a basic request. This makes it possible to generate poems, articles and other text. Open AI’s DALL-E 2 generates photorealistic images and art through natural language input.

• As organizations shift to virtual meetings on Zoom and Microsoft Teams, there’s often a need for a transcript of the conversation.
• It also open-sourced a game — The Mystery of the Three Bots — on GitHub to show how a small model and a data set created with Semantic Reactor might be used to drive conversations with game characters.
• The uses of AC in the world of business are yet to be fully explored.
• Fluree brings trust and security to that data, which mitigates risk and extends data governance into unstructured enterprise information.
• In every instance, the goal is to simplify the interface between humans and machines.
• By integrating AtScale’s Semantic Layer and Query Engine with large language models (LLMs), AtScale has set a new standard in Text-to-SQL accuracy, achieving an impressive 92.5% across all combinations of question and schema complexities.

Personal assistants like Siri, Alexa and Microsoft Cortana are prominent examples of conversational AI. They allow humans to make a call from a mobile phone while driving or switch lights on or off in a smart home. Increasingly, these systems understand intent and act accordingly. For example, chatbots can respond to human voice or text input with responses that seem as if they came from another person. What’s more, these systems use machine learning to constantly improve.

This will likely translate into systems that understand more complex language patterns and deliver automated but accurate technical support or instructions for assembling or repairing a product. Concerns about natural language processing are heavily centered on the accuracy of models and ensuring that bias doesn’t occur. The idea of machines understanding human speech extends back to early science fiction novels. These include language translations that replace words in one language for another (English to Spanish or French to Japanese, for example). For example, NLP can convert spoken words—either in the form of a recording or live dictation—into subtitles on a TV show or a transcript from a Zoom or Microsoft Teams meeting. Yet while these systems are increasingly accurate and valuable, they continue to generate some errors.