This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Today’s business landscape is arguably more competitive and complex than ever before: Customer expectations are at an all-time high and businesses are tasked with meeting (or exceeding) those needs, while simultaneously creating new products and experiences that will provide consumers with even more value. At the same time, many organizations are strapped for resources, contending with budgetary constraints, and dealing with ever-present business challenges like supply chain latency.
The transition to online communication—from sales calls to internal meetings to educational coursework—has created significant opportunities for new AI-powered tools and platforms that help individuals fully use all this digital data. One predominant AI feature that has risen in popularity is AI-powered transcript summarizers. In addition to providing an immediate transcript of a virtual meeting or lecture (using AI speech-to-text ), AI transcript summarizers can summarize th
Anthropic has just released Claude 3.5, a powerful new version of its LLM series. While this model brings improved reasoning and coding skills, the real excitement centers around a new feature called “Computer Use.” This capability lets developers guide Claude to interact with the computer like a person—navigating screens, moving cursors, clicking, and typing.
In recent years, the surge in large language models (LLMs) has significantly transformed how we approach natural language processing tasks. However, these advancements are not without their drawbacks. The widespread use of massive LLMs like GPT-4 and Meta’s LLaMA has revealed their limitations when it comes to resource efficiency. These models, despite their impressive capabilities, often demand substantial computational power and memory, making them unsuitable for many users, particularly
Start building the AI workforce of the future with our comprehensive guide to creating an AI-first contact center. Learn how Conversational and Generative AI can transform traditional operations into scalable, efficient, and customer-centric experiences. What is AI-First? Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
Building AI applications with speech recognition should be straightforward: process audio, get structured data, take action. Yet despite the industry's claims of +90% accuracy, developers face a persistent challenge: the gap between raw audio files and reliable, structured outputs. The hidden cost of "good enough" speech-to-text Consider a simple example: Your application needs to parse "sarah.johnson@acme-corp.com" from an audio stream.
Many app developers are interested in building on device experiences that integrate increasingly capable large language models (LLMs). Running these models locally on Apple silicon enables developers to leverage the capabilities of the user's device for cost-effective inference, without sending data to and from third party servers, which also helps protect user privacy.
Many app developers are interested in building on device experiences that integrate increasingly capable large language models (LLMs). Running these models locally on Apple silicon enables developers to leverage the capabilities of the user's device for cost-effective inference, without sending data to and from third party servers, which also helps protect user privacy.
AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. Many businesses want to integrate these cutting-edge AI capabilities with their existing collaboration tools, such as Google Chat, to enhance productivity and decision-making processes.
Last Updated on October 31, 2024 by Editorial Team Author(s): Jonas Dieckmann Originally published on Towards AI. Data analytics has become a key driver of commercial success in recent years. The ability to turn large data sets into actionable insights can mean the difference between a successful campaign and missed opportunities. However, data quality is still a major challenge: if the data that is fed into a model lacks quality/consistency, the resulting output will also be of low quality.
Amy Brown , a former healthcare executive, founded Authenticx in 2018 to help healthcare organizations unlock the potential of customer interaction data. With two decades of experience in the healthcare and insurance industries, she saw the missed opportunities in using customer conversations to drive business growth and improve profitability. Authenticx addresses this gap by utilizing AI and natural language processing to analyze recorded interactions—such as calls, emails, and chats—providing
IBM Build Partner Inspire for Solutions Development is a regional consulting firm that provides enterprise IT solutions across the Middle East. Jad Haddad , Head of AI at Inspire for Solutions Development has embraced the IBM watsonx™ AI and data platform to enhance the HR experience for its 450 employees. Next-gen HR for a next-gen workforce As a new generation of digital natives enters the workforce, we are seeing new expectations around the employee experience.
Today’s buyers expect more than generic outreach–they want relevant, personalized interactions that address their specific needs. For sales teams managing hundreds or thousands of prospects, however, delivering this level of personalization without automation is nearly impossible. The key is integrating AI in a way that enhances customer engagement rather than making it feel robotic.
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! As we wrap up October, we’ve compiled a bunch of diverse resources for you — from the latest developments in generative AI to tips for fine-tuning your LLM workflows, from building your own NotebookLM clone to instruction tuning. We’re also excited to share updates on Building LLMs for Production, now available on our own platform: Towards AI Academy.
A new AI-powered, imaging-based technology that creates accurate three-dimensional models of tumors, veins and other soft tissue offers a promising new method to help surgeons operate on, and better treat, breast cancers. The technology, from Illinois-based startup SimBioSys, converts routine black-and-white MRI images into spatially accurate, volumetric images of a patient’s breasts.
Last Updated on October 31, 2024 by Editorial Team Author(s): Kamran Khan Originally published on Towards AI. Boost Your Productivity with AI This member-only story is on us. Upgrade to access all of Medium. Photo by BoliviaInteligente on Unsplash In the fast pace of digital today, tools created through AI can work to create changes in being more productive, creative, and even more efficient every day.
Deep learning has made advances in various fields, and it has made its way into material sciences as well. From tasks like predicting material properties to optimizing compositions, deep learning has accelerated material design and facilitated exploration in expansive materials spaces. However, explainability is an issue as they are ‘black boxes,’ so to say, hiding their inner working.
The guide for revolutionizing the customer experience and operational efficiency This eBook serves as your comprehensive guide to: AI Agents for your Business: Discover how AI Agents can handle high-volume, low-complexity tasks, reducing the workload on human agents while providing 24/7 multilingual support. Enhanced Customer Interaction: Learn how the combination of Conversational AI and Generative AI enables AI Agents to offer natural, contextually relevant interactions to improve customer exp
Author(s): Rafe Brena, Ph.D. Originally published on Towards AI. They stayed buried for 20 years This member-only story is on us. Upgrade to access all of Medium. Image by the author using Ideogram I worked on AI full-time for over 30 years, at least 10 of them in an area called “Multiagent Systems,” Intelligent Agents, or simply “Agents,” depending on who you ask.
In the vast world of AI tools, a key challenge remains: delivering accurate, real-time information. Traditional search engines have dominated our digital lives, helping billions find answers, yet they often fall short in providing personalized, conversational responses. Large language models like OpenAI’s ChatGPT transformed how we interact with information, but they were limited by outdated training data, reducing their utility in dynamic, real-time situations.
Learning Python can be difficult. You might spend a lot of time watching videos and reading books; however, if you can’t put all the concepts learned into practice, that time will be wasted. This is why you should get your hands dirty with Python projects. A project will help you bring together everything you’ve learned, stay motivated, build a portfolio, and come up with ways of approaching problems and solving them with code.
In the fast-moving world of artificial intelligence and machine learning, the efficiency of deploying and running models is key to success. For data scientists and machine learning engineers, one of the biggest frustrations has been the slow and often cumbersome process of loading trained models for inference. Whether models are stored locally or in the cloud, inefficiencies during loading can create frustrating bottlenecks, reducing productivity and delaying the delivery of valuable insights.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
Created Using Midjourney Video is rapidly becoming one of the next frontiers in generative AI. From OpenAI’s Sora startups like Runway or Pika to the new efforts from Google, most of the large video generation models remained closed-source. There are open-source efforts such as Stability AI’s Stable Video, but the quality is not at the same level as that of the large commercial alternatives.
Python is the most popular data science programming language, as it’s versatile and has a lot of support from the community. With so much usage, there are many ways to improve our data science workflow that you might not know.
The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.
By Judie Rahman, Senior Solutions Manager at BigHand. BigHand recently surveyed over 800 legal professionals and found 35% of participating law firms confirmed that reviewing.
Speaker: Alexa Acosta, Director of Growth Marketing & B2B Marketing Leader
Marketing is evolving at breakneck speed—new tools, AI-driven automation, and changing buyer behaviors are rewriting the playbook. With so many trends competing for attention, how do you cut through the noise and focus on what truly moves the needle? In this webinar, industry expert Alexa Acosta will break down the most impactful marketing trends shaping the industry today and how to turn them into real, revenue-generating strategies.
Sponsored Content From November 1st to November 21st, 2024 (8:00 am UTC), 365 Data Science offers free access to its comprehensive learning platform. This is.
We organize all of the trending information in your field so you don't have to. Join 15,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
173 
Let's personalize your content