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Implementing AI into Enterprise Search to Make It Smarter

In this sponsored post, our friends over at Sinequa share how the advent of AI, enterprise search has transformed into intelligent search, precisely as was envisaged. This has far-reaching consequences on customer experience and, by extension, return on investment (ROI) in all industries.

Deci delivers breakthrough inference performance on Intel’s 4th Gen Sapphire Rapids CPU

Deci, the deep learning company building the next generation of AI, announced a breakthrough performance on Intel’s newly released 4th Gen Intel® Xeon® Scalable processors, code-named Sapphire Rapids. By optimizing the AI models which run on Intel’s new hardware, Deci enables AI developers to achieve GPU-like inference performance on CPUs in production for both Computer Vision and Natural Language Processing (NLP) tasks.

Originality.AI Allows Users to Quickly Detect AI Written Content With a Chrome Extension 

Originality.AI recently launched a tool that allows users to screen for content created by popular AI tools, such as ChatGPT. To increase efficiency for the user, Originality.AI has also launched a Google Chrome Extension to make it faster and easier to check content.

New Research Shows that 77% of Businesses Using Natural Language Processing Expect to Increase Investment

More than three-quarters of businesses with active natural language processing (NLP) projects plan to increase spending on in the next 12 to 18 months, according to new data from expert.ai, a leading company in artificial intelligence (AI) for language understanding. The finding is one of many data points culled from a recent survey and detailed in expert.ai’s new report, The 2023 Expert NLP Survey Report: Trends driving NLP Investment and Innovation.

Research Highlights: R&R: Metric-guided Adversarial Sentence Generation

Large language models are a hot topic in AI research right now. But there’s a hotter, more significant problem looming: we might run out of data to train them on … as early as 2026. Kalyan Veeramachaneni and the team at MIT Data-to-AI Lab may have found the solution: in their new paper on Rewrite and Rollback (“R&R: Metric-Guided Adversarial Sentence Generation”), an R&R framework can tweak and turn low-quality (from sources like Twitter and 4Chan) into high-quality data (texts from sources like Wikipedia and industry websites) by rewriting meaningful sentences and thereby adding to the amount of the right type of data to test and train language models on.

Snorkel AI Accelerates Foundation Model Adoption with Data-centric AI

Snorkel AI, the data-centric AI platform company, today introduced Data-centric Foundation Model Development for enterprises to unlock complex, performance-critical use cases with GPT-3, RoBERTa, T5, and other foundation models. With this launch, enterprise data science and machine learning teams can overcome adaptation and deployment challenges by creating large, domain-specific datasets to fine-tune foundation models and using them to build smaller, specialized models deployable within governance and cost constraints.

The Move Toward Green Machine Learning

A new study suggests tactics for machine learning engineers to cut their carbon emissions. Led by David Patterson, researchers at Google and UC Berkeley found that AI developers can shrink a model’s carbon footprint a thousand-fold by streamlining architecture, upgrading hardware, and using efficient data centers. 

How to Effectively Leverage LLMs (Large Language Models) for B2B NLP (Natural Language Processing) Use Cases

In this contributed article, Rigvi Chevala, Evalueserve’s CTO, believes that while plenty of investment and progress into AI is causing great strides, ML and AI benefit from simpler solutions. LLMs offer the opportunity for a quick start, and many players are considering how to make them useful to their businesses. The article advises you to count your organization as one of them – understand their benefits and constraints and wisely use them.

Deci’s Natural Language Processing (NLP) Model Achieves Breakthrough Performance at MLPerf

Deci, the deep learning company harnessing Artificial Intelligence (AI) to build better AI, announced results for its Natural Language Processing (NLP) inference model submitted to the MLPerf Inference v2.1 benchmark suite under the open submission track.

Interview: Dr. Susan Hura, Chief Design Officer at Kore.ai

I recently caught up with Dr. Susan Hura, Chief Design Officer at Kore.ai to discuss the bank-end work that goes into developing an intuitive conversational AI-supported chatbot. She’ll also dispel some of the myths behind developing and introducing a CAI-empowered chatbot into a business’s digital platform. Whether used out-of-the-box or customized, a chatbot’s design plays a more strategic role than one might think and requires an immense amount of human input to create.