With increasing scale in model and dataset size, the training of deep neural networks becomes a massive computational burden. One approach to speed up the training process is Selective Backprop. For this approach, we perform a forward pass to obtain a loss value for each data point in a minibatch.…
Welcome insideBIGDATA AI News Briefs Bulletin Board, our timely new feature bringing you the latest industry insights and perspectives surrounding the field of AI including deep learning, large language models, generative AI, and transformers. We’re working tirelessly to dig up the most timely and curious tidbits underlying the day’s most popular technologies. We know this field is advancing rapidly and we want to bring you a regular resource to keep you informed and state-of-the-art. The news bites ar
In this contributed article, Ben Younkman, Regional Director at Village Capital, explores how forward-thinking startups are spearheading data-driven innovation to create digital solutions that increase access to critical services — including the financial, educational and healthcare sectors — resulting in a more equitable and inclusive world.
Welcome insideBIGDATA AI News Briefs Bulletin Board, our timely new feature bringing you the latest industry insights and perspectives surrounding the field of AI including deep learning, large language models, generative AI, and transformers. We’re working tirelessly to dig up the most timely and curious tidbits underlying the day’s most popular technologies. We know this field is advancing rapidly and we want to bring you a regular resource to keep you informed and state-of-the-art. The news bites ar
Data augmentation is vital for object detection tasks that require expensive bounding box annotations. Recent successes in diffusion models have inspired the use of diffusionbased synthetic images for data augmentation. However, existing works have primarily focused on image classification, and…
Activity classification has become a vital feature of wearable health tracking devices. As innovation in this field grows, wearable devices worn on different parts of the body are emerging. To perform activity classification on a new body location, labeled data corresponding to the new locations…
The recent surge in Large Language Model (LLM) related applications has led to a concurrent escalation in expectations for LLMs to accommodate a myriad of personas and encompass a broad spectrum of perspectives. An important first step towards addressing this demand is to align language models with…
Galileo, a leading machine learning (ML) company for unstructured data, released a Hallucination Index developed by its research arm, Galileo Labs, to help users of today’s leading LLMs determine which model is least likely to hallucinate for their intended application.
MaintainX, a startup that provides software for industrial maintenance, raises $50 million to achieve a zero-downtime future using AI and data. Read the exclusive interview with the CEO and the lead investor.
Businesses will face substantial competitive hurdles if they are not Generative AI-ready in the next few years; Report is the first to offer a generative AI scorecard for 2024 readiness. "The State of Generative AI Insiders Report," in conjunction with leaders from Insight Partners, Battery Ventures, Dataiku, Weights & Biases and Glean, was unveiled highlighting market challenges inherent with implementing generative AI in a scalable, profitable way.
This paper proposes a framework leveraging small samples from different Automatic Speech Recognition (ASR) data sources to predict model performance and facilitate ASR data selection decisions. By utilizing data distribution distance and a mapping technique inspired by neural scaling laws, our…
While data selection methods have been studied extensively in active learning, data pruning, and data augmentation settings, there is little evidence for the efficacy of these methods in industry scale settings, particularly in low-resource languages. Our work presents ways of assessing prospective…
Available starting today, Databricks' new tools address key challenges in developing production-grade LLM apps, right from serving real-time business data to combining that data with the right model and subsequent monitoring.
Offline Reinforcement Learning (RL) has emerged as a promising approach to address real-world challenges where online interactions with the environment are limited, risky, or costly. Although, recent advancements produce high quality policies from offline data, currently, there is no systematic…
In the financial quarter ending September, when VAST Data announced its unified data platform, the company's cumulative software bookings surpassed $1 billion.
The main challenge of offline reinforcement learning, where data is limited, arises from a sequence of counterfactual reasoning dilemmas within the realm of potential actions: What if we were to choose a different course of action? These circumstances frequently give rise to extrapolation errors,…
While SuperDuperDB is just a few months old, it has already drawn significant traction from major data ecosystem players, including Snowflake, BigQuery and MongoDB.
In this continuing regular feature, we give all our valued readers a monthly heads-up for the top 10 most viewed articles appearing on insideBIGDATA. Over the past several months, we’ve heard from many of our followers that this feature will enable them to catch up with important news and features flowing across our many channels.
Our friends over at PwC released its 2023 Emerging Technology Survey, unveiling the seismic impact emerging technologies have on top-performing companies and highlighting the critical role of AI in driving business model reinvention and long-term innovation.
Intuit has stood out among enterprise companies for its speed and adeptness at deploying the generative AI. Intuit's VP of Product Management walks through step-by-step how to get to the perfect data layer to make generative AI work.
Genpact announced an industry-first playbook: FMOps – The Generative AI Imperative for Production. The playbook, which focuses on Foundation Model Operations (FMOps), provides practical guidelines for building solid and efficient foundations for generative AI solutions.
