SAS' Mary Osborne, Ali Dixon Ricke, and Franklin Manchester break down what insurers still need to learn about generative AI.
We often hear about cyberattacks, hackers, ransomware, and other nefarious deeds in the news, but not all data breaches are caused by third parties.
When using LLMs, managing toxicity, bias, and bad actors is critical for trustworthy outcomes. Let’s explore what organizations should be thinking about when addressing these important areas.
Adding linguistic techniques in SAS NLP with LLMs not only help address quality issues in text data, but since they can incorporate subject matter expertise, they give organizations a tremendous amount of control over their corpora.
In a previous blog post, we discussed how generative AI (GenAI) is experiencing unprecedented popularity, with organizations across various industries eager to unlock its immense potential. We also highlighted potential use cases organizations must identify to unlock GenAI's full potential with credit customer journeys. These can include using chatbots for
Generative AI (GenAI) is in its most popular era and many organisations across industry are looking for ways to unlock its potential value. McKinsey's projections suggest that GenAI could add a staggering $2.6 to $4.4 trillion in value to the global economy. In fact, banking is the number one industry
Across the world, investigators and law enforcement officers are tackling a rapidly evolving and expanding workload fueled by an increase in complex modern-day crimes. As technology alters the type and methodology of the crime itself – the evasion of tax payments, theft of public funds, erroneous disbursement of benefits, gaming
SAS' Federica Citterio answers the perennial data science question: "How can I trust (generative) LLM to provide a reliable, non-hallucinated result?"
The ability of an organization to make informed decisions swiftly and accurately is crucial. Organizations across various industries rely heavily on advanced technologies to navigate complex data and enhance customer experiences. Decision trees and large language models (LLMs) are two technologies that play pivotal roles in empowering organizations to make
Imagine if your job was to sort a massive pile of 40,000 stones into about 200 buckets based on their unique properties. Each stone needs to be carefully examined, categorized and placed in the correct bucket, which takes about five minutes per stone. Fortunately, you’re not alone but part of
While large language models (LLMs) have become synonymous with advanced AI capabilities, their integration into various business and technological domains is often accompanied by significant costs. These costs arise from the extensive computational resources required for training and running these models. However, traditional natural language processing (NLP) techniques offer a
See why we think the use of AI assistants will take off in 2024.
In a global economy marked by fragile supply chains, scarce resources and rising energy costs, the spotlight is on forecasting to address these issues. In 2022, McKinsey & Company uncovered a staggering $600 billion annual food waste, equating to 33% – 40% of global food production, spotlighting the devastating consequences
Recently, we sat down with Jakob Koziel, Senior Research Analyst at Bissell Centre. During their conversation, Jakob highlighted some of the work Bissell Centre is doing to eradicate poverty in Edmonton and how SAS is helping them move their mission forward. Question: Give me a little bit of background on
La información que los organismos policiales almacenan sobre detenciones o incidentes delictivos, así como los avisos a los departamentos de policía, tienen un valor enorme para resolver futuros casos que se pueden plantear. Analizar manualmente esta gran cantidad de datos en busca de patrones puede llevar mucho tiempo y sus
In today's world, data-driven systems make significant decisions across industries. While these systems can bring many benefits, they can also foster distrust by obscuring how decisions are made. Therefore, transparency within data driven systems is critical to responsible innovation. Transparency requires clear, explainable communication. Since transparency helps people understand how
SAS' Ali Dixon and Mary Osborne reveal why a BERT-based classifier is now part of our natural language processing capabilities of SAS Viya.
Editor's note: This article follows Curious about ChatGPT: Exploring the origins of generative AI and natural language processing. As ChatGPT has entered the scene, many fears and uncertainties have been expressed by those working in education at all levels. Educators worry about cheating and rightly so. ChatGPT can do everything
How did we get to a place where a conversational chatbot can quickly create a personalized letter? Join us as we explore some of the key innovations over the past 50 years that help inform us about how to respond and what the future might hold.
SAS' Kirk Swilley and Tom Sabo showcase how you can use perform text analysis on minimal structured narrative data to spot patterns of possible human trafficking.
ChatGPT from OpenAI has changed how the general public thinks about AI. What does this mean for analytics practitioners?
Using such features and Natural Language Processing capabilities like text parsing and information extraction in SAS Visual Text Analytics (VTA) helps us uncover emerging trends and unlock the value of unstructured text data.
To find exact duplicates, matching all string pairs is the simplest approach, but it is not a very efficient or sufficient technique. Using the MD5 or SHA-1 hash algorithms can get us a correct outcome with a faster speed, yet near-duplicates would still not be on the radar. Text similarity is useful for finding files that look alike. There are various approaches to this and each of them has its own way to define documents that are considered duplicates. Furthermore, the definition of duplicate documents has implications for the type of processing and the results produced. Below are some of the options. Using SAS Visual Text Analytics, you can customize and accomplish this task during your corpus analysis journey either with Python SWAT package or with PROC SQL in SAS.
In the face of rapid digitalization and modernization, data scientists in Cameroon joined the SAS Hackathon seeking a way to preserve indigenous African languages.
A cancer journey affects both physical and mental health. This often results in feelings of social isolation, loss of identity, clinical depression and even PTSD. This often goes unrecognized and undiagnosed due in part to lack of resources, tools and time. Swedish startup War On Cancer wondered whether they could
Corpus analysis is a technique widely used by data scientists because it provides an understanding of a document collection and provides insights into the text.
The 2021 SAS Hackathon was a major success and teams are now signing up for the 2022 hackathon. We are inviting you to join us. The world has lots of problems in search of answers and it’s your chance to contribute some creative solutions. Here’s what the team from KPMG
Technological advancements in connectivity and global positioning systems (GPS) have led to increased data tracking and related business use cases to analyze such movements. Whether analyzing a vehicle, an animal or a population's movements - each use case requires analyzing underlying spatial information. Global challenges such as virus outbreaks, deforestation
El texto no estructurado es la mayor fuente de datos generada por el ser humano y crece exponencialmente cada minuto. No hay que olvidar que la tecnología está ya presente en todos los aspectos de nuestras vidas, tanto profesionales como personales, y nos permite conversar rápidamente a través de textos,
Conversational AI can offer a way to provide that always-on 24/7, fast, convenient experience that can go anywhere (phone, computer smart speakers, even your car). It can provide a human-like experience through real-time, personalized interaction with AI running in the background. This technology is being applied across many industries for a variety of use cases (both customer-facing and for internal use).
