CDW Healthcare’s Post

Ready to wade deeper into the #GenAI waters? Take a look at how incorporating multimodal language models can make a huge impact for your patients and staff. https://cdw.social/3YnAn0C #AI #MachineLearning #HealthIT

The world doesn't need more language models! https://lnkd.in/eYbFtgzV KunavvKnowsAI #kunavvai #genai #ai #thoughtleardership #aitechnology #businessinnovattion #disruptivetechnologies

Discover the transformative potential of Large Language Models (LLMs) in multimodal AI applications! Our latest blog explores how integrating LLMs with other AI models can enhance industry user experiences. Read More: https://lnkd.in/d6xfkV8z #AI #LLM #GenAI

77% of enterprises are using SLMs in production according to Tomasz Tunguz 💪 There are so many misconceptions about Small Language Models, from how they work to what they excel at and when to use them. At Arcee.ai, we've dived deep into these questions and are excited to share our insights with the blog attached! 🚀 Key Takeaways:📝 Not All SLMs Are Created Equal 🧠 - Each model has its unique strengths and limitations. 🤠 Test public benchmarks from trusted sources like Hugging Face, or better yet, conduct your own tests! A true SLM is a Secure Solution You Own, with Less Maintenance vs. LLMs - otherwise just continue to rent a closed source model.. Check out our blog for a detailed breakdown and actionable insights: 📚 🌐 #AI #MachineLearning #SmallLanguageModels #ArceeAI #TechInsights 🚀💪 https://lnkd.in/ehbnRjUs

Think AI language agents aren't that smart? Think again! AI language agents are evolving too fast, and they might be smarter than you think. Here are 5 reasons why: - Rapid Improvement: AI models have shown exponential improvement. For instance, GPT 3.5 scored in the bottom 10% of the bar exam, while GPT 4.0 scored in the top 10% just four months later. - Specialized Expertise: AI agents are becoming experts in specific domains. Google’s MedLM reached expert performance on medical licensing exam-style questions. - Artificial General Intelligence (AGI): Even though now we are far from AGI, where AI can learn, understand, and apply knowledge across various tasks as effectively as humans, most likely we’ll see a form of AGI developed in the future. - Recursive Self-Improvement: One of the most pivotal advancements is AI's ability to improve its own results. This recursive self-improvement could lead to unpredictable advancements, pushing AI capabilities beyond human control. - Artificial Superintelligence (ASI): The ultimate milestone is ASI, where AI surpasses human intelligence across all cognitive tasks. Imagine an AI smarter than the combined cognitive power of all humans. This isn't just science fiction; it's a potential future. AI Agents is showing us both incredible opportunities and significant risks. That’s why we have to develop them carefully. Few things I think we have to have in mind when building such agents: - Human in the loop – always have a human that takes the final decision - Carefully give them access for writing purposes – we have to think twice before giving them full write access to our systems - Reviewer Agent – have another agent that reviews the output and gives a red or green flag to execute tasks - Use Different AI Models – use different AI models in your Agent workflow to mitigate the risk of biased decisions What do you think is the most exciting or concerning aspect of AI's rapid advancement? ____________________________ Our vision at Cubeo AI is to build a no-code platform for building autonomous AI Teams.  Build your AI Assistants and create an AI Team in minutes with our no-code solution Here👉: https://lnkd.in/eZ2EzpQY You only need an email address to sign-up and start building without any coding! #cubeoai #ai #artificialintelligence #chatgpt #sales #marketing #aiagents #aiautonomousagents

🌐 SLMs Gaining Ground While LLMs Reach for the Stars 🌐 Forbes recently shared insights on the rising popularity of Small Language Models (SLMs), which are proving to be a powerful alternative to Large Language Models (LLMs). SLMs are carving a niche by offering efficient, scalable AI that’s accessible for more applications, even those with limited resources. Meanwhile, LLMs continue to push boundaries in complex analysis and creative generation. This shift highlights the strength in both models: SLMs bring speed and targeted impact, while LLMs drive deep, expansive insights. The future of AI lies in strategically leveraging each, based on the unique demands of the business. #AI #SLMs #LLMs #DigitalStrategy #Innovation https://lnkd.in/gmSbsan3

Word Error Rate (WER) is a metric that evaluates the performance of ASR systems by analyzing the accuracy of speech-to-text transcripts. Yet, there’s a growing concern that benchmarks fail to represent real-world use cases, resulting in disappointing ASR performance in enterprise products and apps. In a market flooded with contradictory private benchmarks, there’s also the risk of overlooking great speech recognition alternatives due to commercial bias. This new article answers the key question - should you trust WER? To answer, we look at the most common ASR benchmarks, highlight their limitations in assessing speech AI systems in real-life scenarios, and provide hands-on insights and tips on how to circumvent the benchmark limitations when assessing a speech-to-text model or provider. #asr #benchmakrs #wer #ai #speechrecognition

Love this. I'm captivated by the potential power of AI, but also wary of the operational requirements to support and maintain what you build. Small language models are a way to get teams moving with AI in a controlled way. The power would be in selecting discreet use cases to implement and monitor so you can measure what needles you are moving with AI and why. AI is going to be an operational overlay on almost everything we do, whether we know it or not. The process starts with small, measurable POCs that teams can organize around, learn from and grow from. https://lnkd.in/gew9cjrE

❓ Deciding between two directions of gen #AI adoption? We’ve highlighted the strengths and weaknesses of larger and smaller language models to help you choose ⬇️ Read our new article to get a clear vision of large language models vs. small language models standoff > https://lnkd.in/eV_StKgf #instinctools_services #genAI #softwaredevelopment #artificialintelligence #softwaredevelopmentcompany

Discover how #languagemodels are shaping the future of technology.  Explore how they generate text, understand language nuances, and even assist in various tasks. Click here https://lnkd.in/gkPH3hzz #ai #ml #llms #generativeai #dataanalysis #digitaltransformation