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With the release of DeepSeek V3 and R1, U.S. tech giants are struggling to regain their competitive edge. Now, DeepSeek has introduced Janus Pro, a state-of-the-art multimodal AI that further solidifies its dominance in both understanding and generative AI tasks. Janus Pro outperforms many leading models in multimodal reasoning, text-to-image generation, and instruction-following benchmarks.
Ericsson has launched Cognitive Labs, a research-driven initiative dedicated to advancing AI for telecoms. Operating virtually rather than from a single physical base, Cognitive Labs will explore AI technologies such as Graph Neural Networks (GNNs), Active Learning, and Large-Scale Language Models (LLMs). According to Ericsson, these innovations form the backbone of the companys solutions for the next generation of mobile communications and signal the companys commitment to extending AIs transfo
The rise of large language models (LLMs) has spurred the development of frameworks to build AI agents capable of dynamic decision-making and task execution. Two prominent contenders in this space are smolagents (from Hugging Face) and LangGraph (from LangChain). This article delves into the features and capabilities of both these models, providing a detailed comparison […] The post Smolagents vs LangGraph: A Comprehensive Comparison of AI Agent Frameworks appeared first on Analytics Vidhya
BOW , the trailblazing universal robotics software company, has secured 4 million in a seed fundin g round led by Northern Gritstone. The round included co-investors Finance Yorkshire and Praetura Ventures , as part of the Northern Powerhouse Investment Fund II. This pivotal investment will accelerate the development of BOWs innovative platform and software development kit (SDK), making it easier than ever for developers to program and manage robotics applications across any platform or robot mo
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 Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
Move over OpenAI, there’s a new disruptor in town! DeepSeek has been making AI headlines worldwide, causing market tremors and shaking up Silicon Valley. In a dramatic turn of events, DeepSeeks latest AI breakthroughs have even wiped nearly $1 trillion off major tech stocks. If thats not a mic drop moment, what is? But how […] The post Evolution of DeepSeek: How it Became a Global AI Game-Changer!
Artificial Intelligence (AI) transforms how we solve problems and make decisions. With the introduction of reasoning models, AI systems have progressed beyond merely executing instructions to thinking critically, adapting to new scenarios, and handling complex tasks. These advancements significantly impact industries such as healthcare, finance, and education.
Artificial Intelligence (AI) transforms how we solve problems and make decisions. With the introduction of reasoning models, AI systems have progressed beyond merely executing instructions to thinking critically, adapting to new scenarios, and handling complex tasks. These advancements significantly impact industries such as healthcare, finance, and education.
The Qwen family of vision-language models continues to evolve, with the release of Qwen2.5-VL marking a significant leap forward. Building on the success of Qwen2-VL, which was launched five months ago, Qwen2.5-VL benefits from valuable feedback and contributions from the developer community. This feedback has played a key role in refining the model, adding new […] The post Qwen2.5-VL Vision Model: Features, Applications, and More appeared first on Analytics Vidhya.
Qsic , the intelligent in-store audio platform redefining the retail experience, has announced the successful close of a $25 million Series B funding round led by Hedosophia. The funding will be used to accelerate the platforms AI-driven capabilities, expand into new retail locations, and enhance its ability to boost in-store sales while unlocking new revenue streams for retailers.
OpenAI was the first to introduce reasoning models like o1 and o1-mini, but is it the only player in the game? Not by a long shot! Chinese LLMs like DeepSeek, Qwen, and now Kimi are stepping up to challenge OpenAI by delivering similar capabilities at much more affordable prices. After DeepSeek’s impressive debut, it’s Kimi […] The post Kimi k1.5 vs OpenAI o1: Is it Worth Spending $20 for ChatGPT Plus?
In our modern age, communities face several emerging threats to public safety: rising urbanization, increased crime rates and the threat of terrorism. When addressing the combination of constrained law enforcement resources and growing cities, the challenge of ensuring public safety becomes even more difficult. Advancements in technology have allowed for monitoring devices and cameras to make public spaces safer but this often comes as a cost.
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.
AI agents allow employees to engage with complex systems conversationally while enabling those systems to communicate with each other in ways previously impossible. The journey to agent-enabled operations starts with clarity on business objectives. COOs have the opportunity to serve as the connective tissue between technical and business stakeholders, by working with CTOs on agent architecture, business leaders on use case identification, and HR leaders on culture transformation.
Alan Ranger is the VP of Marketing at Cognigy, with a career spanning 30 years, Alan has held a variety of sales, marketing and leadership roles, both in start-up and large enterprise software companies. Before joining Cognigy, he led global market development at LivePerson where, during his six-year tenure, revenues doubled from $223m to $470m. As Cognigys VP Marketing, Alans focus is on leading and inspiring his high-performance global team to deliver programmes across branding, product market
Evaluating large language models (LLMs) is crucial as LLM-based systems become increasingly powerful and relevant in our society. Rigorous testing allows us to understand an LLMs capabilities, limitations, and potential biases, and provide actionable feedback to identify and mitigate risk. Furthermore, evaluation processes are important not only for LLMs, but are becoming essential for assessing prompt template quality, input data quality, and ultimately, the entire application stack.
A new research collaboration between Israel and Japan contends that pedestrian detection systems possess inherent weaknesses, allowing well-informed individuals to evade facial recognition systems by navigating carefully planned routes through areas where surveillance networks are least effective. With the help of publicly available footage from Tokyo, New York and San Francisco, the researchers developed an automated method of calculating such paths, based on the most popular object recognition
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): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This weeks AI discourse centered on DeepSeeks r1 release, which sparked a heated debate about its implications for OpenAI, GPUs, and the broader industry. Meanwhile, Google quietly rolled out an improved version of its own reasoning model Gemini Flash 2.0 Thinking, improving its AIME benchmark score to 73.3% (from ~64% in December).
Boston-based dental AI innovator VideaHealth has successfully raised $40 million in an oversubscribed Series B funding round, further cementing its position as a leader in artificial intelligence solutions for the dental industry. This milestone funding round, led by Threshold Ventures with participation from Avenir Ventures , BAM Ventures , and existing backers like Spark Capital , Zetta Venture Partners , and Pillar VC , comes at a time when AI-driven healthcare solutions are more critical tha
Scaling the capacity of language models has consistently proven to be a reliable approach for improving performance and unlocking new capabilities. Capacity can be primarily defined by two dimensions: the number of model parameters and the compute per example. While scaling typically involves increasing both, the precise interplay between these factors and their combined contribution to overall capacity remains not fully understood.
In production generative AI applications, responsiveness is just as important as the intelligence behind the model. Whether its customer service teams handling time-sensitive inquiries or developers needing instant code suggestions, every second of delay, known as latency, can have a significant impact. As businesses increasingly use large language models (LLMs) for these critical tasks and processes, they face a fundamental challenge: how to maintain the quick, responsive performance users expe
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
Author(s): Dimitris Effrosynidis Originally published on Towards AI. Efficient Retrieval for RAG Leveraging Dense BM25 and Transformer Models This member-only story is on us. Upgrade to access all of Medium. Image by author. Efficient and accurate text retrieval is a cornerstone of modern information systems, powering applications like search engines, chatbots, and knowledge bases.
Author(s): Harsh Maheshwari Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Created using Dalle 3 In the world of Large Language Models (LLMs), Retrieval Augmented Generation (RAG) has emerged as a game-changer. Traditional RAG, while groundbreaking, often follows a predictable pattern: fetch information based on a users query, then use that information to generate a response.
AI startup developed a top system by relying on inexperienced engineers and a loophole in U.S. export controls SINGAPORETake a team of young Chinese engineers, hired by a boss with disdain for experience.
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.
January has been notable for the number of important announcements in AI. For me, two stand out: the US governments support for the Stargate Project, a giant data center costing $500 billion, with investments coming from Oracle, Softbank, and OpenAI ; and DeepSeeks release of its R1 reasoning model , trained at an estimated cost of roughly $5 milliona large number but roughly one-tenth what it cost OpenAI to train its o1 models.
Author(s): Carlos da Costa Originally published on Towards AI. Lay the foundation for your machine learning journey with this comprehensive introduction This member-only story is on us. Upgrade to access all of Medium. Photo by Arseny Togulev on Unsplash When we hear about Machine Learning, our minds often jump to exciting technologies like ChatGPT, Gemini, and other generative AI tools.
Chinese engineer Liang Wenfeng built the AI company after founding a successful hedge fund Some call him Chinas Sam Altman. Others compare him to Jim Simons, the pioneer of quantitative investing.
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.
Did you know that consistent branding can boost a company's revenue by up to 33% ? Yet, creating a professional logo often feels out of reach for many small businesses due to time, cost, and design hurdles. But that's where Turbologo steps in. It's an AI logo maker designed to help you effortlessly create a professional logo in minutes! In this Turbologo review, I'll discuss the pros and cons, what it is, who it's best for, and its key features.
An artificial intelligence model has created a new protein that researchers say would have taken 500 million years to evolve in nature — if nature were capable of producing such a thing.
With the current conversation about widespread LLMs in AI, it is crucial to understand some of the basics involved. Despite their general-purpose pretraining in developing LLMs, most require fine-tuning to excel in specific tasks, domains, or applications. Fine-tuning tailors a model’s performance, making it efficient and precise for specialized use cases.
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