Nextgov/FCW’s Post

Intelligence agencies are using generative AI to build on existing capabilities within intelligence agencies that date back more than a decade, including human language translation and transcription and data processing. Learn more at: https://loom.ly/Sg1Rf8U #GenerativeAI #AI #Intelligence

🚀 Enhancing AI Accuracy with Retrieval-Augmented Generation (RAG) 🚀 We're excited to share our latest insights on how RAG is revolutionizing the way AI models deliver accurate, relevant, and reliable information. Learn how this cutting-edge technology addresses the common challenges faced by Large Language Models (LLMs) and enhances their performance. 🔍 Discover the benefits of RAG: Cost-effective implementation Up-to-date information Enhanced user trust Greater developer control 🔗 Read the full blog to dive deep into the transformative potential of RAG: At Beneficial Technology, our team of experts can help you leverage RAG to power your company's AI adoption and drive growth. Get in touch to learn more! #AI #MachineLearning #Technology #Innovation #RAG #LLM #DataScience #TechTrends #AIAccuracy #BeneficialTechnology

Revolutionize Your Information Retrieval with Multi-Hop Question Answering!🚀 Are you ready to enhance your Question Answering systems? Dive into the world of Multi-Hop Question Answering with the power of LLMs and Knowledge Graphs. Why It Matters: Combining Language Models (LLMs) like #GPT-4 with Knowledge Graphs is transforming how we understand and retrieve complex information. This fusion enables systems to reason through multiple layers of data, delivering precise and insightful answers to intricate queries. How It Works: #LLMs leverage their expansive language capabilities to interpret and connect information from various sources. #KnowledgeGraphs provide structured data that supports efficient multi-hop reasoning, enhancing the depth and accuracy of responses. Real-World Impact: From healthcare to finance, and education, this advanced technology is making significant strides across diverse fields, setting a new standard for information retrieval and analysis. Discover the potential of Multi-Hop Question Answering in our article: 👉 https://lnkd.in/e-3mPvNX Start improving your AI systems today! #AI #LLM #DataScience #DataAnalysis #ArtificialIntelligence #Innovation #WisecubeAI #QuestionAnswering #TechTrends

This Nature Article discussing the multiple uses of various #AI tools in policymaking nails the argument on the head. There are currently no viable AI solutions without skilled professionals to accompany them. This article rightly suggests that AI is mainly good at adding #productivity to the otherwise busy days of policy advisors. The same applies to many other roles in the knowledge economy where highly-trained individuals with a scientific background are now able to harness AI to meet their deadlines quicker and in a more informed manner. In other words, professionals in the knowledge economy should not worry about job prospects as their  #criticalthinking skills will be valued for many years to come. Among others, this piece also explores the many facets of how such AI technologies might be used constructively, to create tools that sift and summarize scientific evidence for policymaking. As part of the discussion around the summarisation of evidence, very little space is devoted to discussing the benefits of using #NLP (natural language processing) algorithms for extractive summarisation, as a more reliable approach to creating summaries of scientific studies, which does not hallucinate, unlike LLMs. In any event, there is a bright future for any skilled professionals who will learn to harness the tools afforded by AI, particularly, if they can combine them to save time in preparing scientific evidence in a manner that is ready to be analysed.  #aisummarisation  #productivity #scicomms #sciencepolicy #evidencebased https://lnkd.in/e7vCJcw9

🤖🧠 Breaking AI News: Unlocking the Potential of AI in Ghana's NSMQ! 📚🔍 Artificial Intelligence is on the brink of another groundbreaking achievement: conquering the prestigious National Science and Maths Quiz (NSMQ) in Ghana. The NSMQ AI project, an open-source endeavor, is creating an intelligent system poised to compete live and emerge victorious in the NSMQ arena. The NSMQ, an annual spectacle of intellect and innovation, serves as the ultimate stage for senior secondary school students in Ghana to display their scientific and mathematical prowess. Three teams, each consisting of two brilliant minds, engage in an exhilarating contest across diverse domains spanning biology, chemistry, physics, and mathematics. The event is organized into five rounds across five progressive stages, culminating in the crowning of a triumphant team that gets to hold the title for a year. 🔬📊 Tackling Unprecedented Technical Challenges Embarking on this ambitious quest, AI experts are boldly confronting a plethora of intricate technical challenges. The exploration spans the intricacies of speech-to-text and text-to-speech technologies, unraveling the enigmas of question-answering algorithms, and refining the delicate art of seamless human-computer interaction. Each challenge serves as a stepping stone, propelling AI toward unprecedented levels of excellence. 🚀 Embarking on a Journey of Achievement The voyage embarked upon in January 2023 has yielded remarkable progress. Let's delve into the pivotal milestones of the NSMQ AI project: Teams in the Spotlight: Diverse teams, each specialized in a unique facet of AI mastery, unite in synergy. From linguistic virtuosos to machine learning maestros, these teams converge to forge an all-encompassing AI contender. Progress Update: The unwavering dedication of these teams has borne fruit, yielding significant advancements across various AI components. The power of natural language processing has been harnessed, the cognitive prowess of AI has been honed, and its strategic acumen fine-tuned. Roadmap to Glory: Gazing resolutely toward the future, the path ahead is clear. Upcoming stages encompass rigorous testing, strategic refinement, and meticulous optimization, culminating in the grand unveiling at the NSMQ 2023 event. 📆 Countdown to Debut: October 2023 Preparations are in full swing for an awe-inspiring debut that promises to leave an indelible mark on education's landscape. The potential of AI extends beyond the NSMQ stage, envisioning a future where millions of students across Africa tap into the benefits of personalized one-on-one learning support. This revolutionary educational transformation is not a distant dream – it's an imminent reality. Source: https://lnkd.in/dUgUQzvQ #DataScience  #AI #Innovation #Technology #MachineLearning Don't forget to sign-up! →https://bit.ly/43SfDO3 Follow Wand for #ai and #dataanalytics daily content! 👇

insightful article on LLM & AI research paper

LLMs have revolutionized the field of AI, demonstrating remarkable capabilities in natural language processing and generation. However, off-the-shelf LLMs struggle with: 1️⃣ 𝐋𝐚𝐜𝐤 𝐨𝐟 𝐩𝐫𝐨𝐩𝐫𝐢𝐞𝐭𝐚𝐫𝐲 𝐜𝐨𝐦𝐩𝐚𝐧𝐲 𝐤𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞  2️⃣ 𝐒𝐭𝐫𝐮𝐠𝐠𝐥𝐢𝐧𝐠 𝐭𝐨 𝐬𝐭𝐚𝐲 𝐮𝐩-𝐭𝐨-𝐝𝐚𝐭𝐞 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐜𝐨𝐧𝐬𝐭𝐚𝐧𝐭 𝐫𝐞𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠 3️⃣ 𝐏𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥 𝐟𝐨𝐫 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐮𝐧𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐞 "𝐡𝐚𝐥𝐥𝐮𝐜𝐢𝐧𝐚𝐭𝐞𝐝" 𝐨𝐮𝐭𝐩𝐮𝐭𝐬 Building structured knowledge sources found in knowledge graphs with LLMs can prevent the above and further amplify LLMs. Read more about our approach that addresses key challenges like knowledge gaps, factual inaccuracies, and lack of context: https://bit.ly/3UkcSSX #Accountability #AI #KnowledgeGraphs #ContextualLLMs #LLMs

🚀 **New Article Alert!** 🚀 Excited to share my latest article on Medium: **"The Hidden Flaws: Why Even the Smartest AI Struggles with Simple Tasks"**. In this piece, I delve into the surprising limitations of Large Language Models (LLMs), exploring why these advanced AI systems often stumble on tasks that are straightforward for humans. 🔍 **Key Highlights:** - The challenges LLMs face in linguistic and common-sense understanding. - Issues with visual-spatial reasoning and basic mathematical tasks. - How LLMs can propagate scientific misconceptions. - The importance of prompt engineering and human oversight. - Strategies for enhancing the reliability and usefulness of LLMs. Whether you’re an AI enthusiast, a tech professional, or just curious about the inner workings of AI, this article offers valuable insights into the current state and future potential of LLMs. Let's connect and discuss how we can collectively improve and harness the power of AI! #AI #MachineLearning #ArtificialIntelligence #Tech #Innovation #LLMs #AIResearch #PromptEngineering #MediumArticle #TechInsights

Vector Databases: Part 3 - Why Are Vector Databases Important to AI? 🤖 Vector databases are essential for AI because they efficiently manage and search through vast amounts of unstructured data. AI models, particularly those used in natural language processing and computer vision, rely on vectorized data for training and inference. These databases enable rapid similarity searches, which are fundamental for tasks like recommendation systems, anomaly detection, and large-scale semantic searches. The ability to handle and process complex data vectors directly accelerates AI development and deployment, making AI applications more robust and scalable. If you'd like to learn more about inference parameters, learn about temperature and top_p. You will get a better understanding of how randomness works with vector based queries. Here's a good article: https://lnkd.in/ekTVHvNa #AI #VectorDatabases #DataScience #Innovation #Technology

The rise of LLMs like GPT, Gemini, Claude and others has sparked renewed interest in knowledge graphs as a complementary technology. LLMs can ingest and learn from knowledge graphs, enhancing their understanding of real-world entities, relationships, and facts. Conversely, knowledge graphs can provide grounding and consistency for LLM outputs, mitigating hallucinations and ensuring factual accuracy. This synergy has led to increased adoption of knowledge graph technology across various domains, including search engines, recommendation systems, question answering, and more. Companies are investing in building large-scale knowledge graphs and integrating them with LLMs to unlock new possibilities and deliver more intelligent and trustworthy AI solutions. As the field of AI continues to evolve rapidly, the combination of knowledge graphs and LLMs is poised to play a pivotal role in pushing the boundaries of what's possible in natural language processing and knowledge representation. Check out this brilliant article from Mike Dillinger, PhD discussing the differences and synergies between the two 👇