Page 33 – Advance Aii

Pramata Launches Contract Agent For Tariff...

With a very timely product launch, Pramata has released a Tariff Risk Analyzer, which uses a contract-focused AI Agent to help you understand and respond to the impact of supply chain disruptions caused by tariff changes. And we’ve certainly seen a lot of that happening recently…! The Analyzer uses a company’s contract data to ‘calculate the impact of newly established tariff structures on supply chain business relationships and then provides recommended next steps to address tariff-related disruptions’. So, what does it cover? Here are some key aspects: ‘Enforcement of contracts: Pramata’s Tariff Risk Analyzer ensures procurement teams can hold vendors accountable to their contractual obligations. Proactive risk assessment: When tariff policies change or vendors attempt to invoke a price adjustment clause, the Tariff Risk Analyzer provides critical insights to enable real-time view of risks through portfolio-wide visualizations, identification of non-standard tariff clauses, missing tariff-protection language, etc. Auto-identification of specific clauses: it doesn’t just search for keywords, it comprehends the legal and commercial intent of contract language – enabling the Tariff Risk Analyzer to automatically identify tariff-related provisions.’ It also offers ‘key insights on high- versus low-risk vendors, notice periods, missing protections’ and users can view contract renewal timelines and create...

Certo ett mobil säkerhetsföretag har nyligen genomfört tester av Venice.ai en ny AI-chatbot som Certo påstår att den har blivit föremål för oro inom cybersäkerhetsvärlden. Venice.ai erbjuder ”ocensurerad” AI-åtkomst vilket innebär att användarna kan få tillgång till en AI som inte begränsas av traditionella innehållsfilter. Detta kan vara en dubbelkantad svärd, medan det öppnar upp för kreativitet och innovation kan det också utgöra en risk för cyberhot. Under testerna lyckades Certo få Venice.ai att generera realistiska phishing-e-postmeddelanden och även fullt fungerande ransomware. Dessa resultat understryker faran med att öppna upp AI för användning utan robusta säkerhetsåtgärder. Genom att erbjuda en plattform där all data förblir på användarens enhet snarare än att lagras på servrar har Venice.ai positionerat sig som en privat och ocensurerad AI-alternativ. Det faktum att hela konversationshistoriken lagras lokalt kan ge en känsla av säkerhet men det eliminerar inte risken för missbruk av teknologin. Enligt rapporter utnyttjar Venice.ai ledande öppen källkod som DeepSeek R1 671B och Llama 3.1 405B för att erbjuda kapabiliteter som kan skapa effektiva cyberhot. Det har blivit populärt i hackarforum där användare rapporterar att de kan generera skräddarsydda phishing-mail och olika typer av malware på bara några minuter. Det finns även exempel på hur...

Mistral has introduced its Agents API, a framework designed to facilitate the development of AI agents capable of executing a variety of tasks including running Python code, generating images, and performing retrieval-augmented generation (RAG). This API aims to provide a cohesive environment where large language models (LLMs) can interact with multiple tools and data sources in a structured and persistent way. Overview of the Agents API The Agents API builds on Mistral’s language models by integrating them with several built-in connectors. These connectors enable agents to execute Python code in a controlled environment, generate images through a dedicated model, access real-time web search, and utilize user-provided document libraries. A key feature is persistent memory, which allows agents to maintain context across multiple interactions, supporting coherent and stateful conversations. Additionally, the API supports agentic orchestration, allowing multiple agents to coordinate or delegate tasks among themselves. This can enable complex workflows, such as having one agent manage code development tasks while another handles documentation or data retrieval. Core Components and Functionality Code Execution: Agents can run Python scripts in a sandbox, supporting activities like data analysis, visualization, or scientific computations. Image Generation: The API leverages Mistral’s FLUX1.1 Ultra model for image creation,...

It seems like every few months, someone publishes a machine learning paper or demo that makes my jaw drop. This month, it’s OpenAI’s new image-generating model, DALL·E. This behemoth 12-billion-parameter neural network takes a text caption (i.e. “an armchair in the shape of an avocado”) and generates images to match it: From https://openai.com/blog/dall-e/. I think its pictures are pretty inspiring (I’d buy one of those avocado chairs), but what’s even more impressive is DALL·E’s ability to understand and render concepts of space, time, and even logic (more on that in a second). In this post, I’ll give you a quick overview of what DALL·E can do, how it works, how it fits in with recent trends in ML, and why it’s significant. Away we go! What is DALL·E and what can it do? In July, DALL·E’s creator, the company OpenAI, released a similarly huge model called GPT-3 that wowed the world with its ability to generate human-like text, including Op Eds, poems, sonnets, and even computer code. DALL·E is a natural extension of GPT-3 that parses text prompts and then responds not with words but in pictures. In one example from OpenAI’s blog, for example, the model renders images from...

Proper Regulation Essential for AI Advancements Proper regulation essential for AI advancements isn’t just a concern for tech insiders—it affects governments, industries, and everyday users worldwide. Artificial intelligence is reshaping everything from education and healthcare to finance and national security. Yet the rapid pace of development has sparked global competition, raising critical questions about accountability, safety, and ethical use. If we want AI to offer long-term benefits without generating serious risks, we must act now with regulatory foresight and coordination. This article explores why creating strong and effective policies around AI is not just beneficial but necessary. Discover how thoughtful regulation can drive innovation, mitigate danger, and create a global digital environment that values fairness and responsibility. Also Read: AI governance trends and regulations Why AI Needs Regulation More Than Ever Artificial intelligence is advancing at an unprecedented rate. Research breakthroughs and commercial releases of generative AI tools like ChatGPT, Midjourney, and DALL·E have made it clear that these tools can generate creative content, solve complex problems, and automate tasks across sectors. This surge in AI capabilities has prompted nations, corporations, and universities to invest heavily in the technology. As this competition intensifies, the race for AI dominance can sometimes...

But Experimental Alternatives Have Problems While ChatGPT-4o – the default AI engine for writing, research and similar work – remains formidable, some problems are cropping up with experimental models. Specifically, ChatGPT-o3, ChatGPT-o4 mini and ChatGPT-o4 mini high – which use advanced reasoning – ‘make-up-facts’ more often when responding to questions from users. Bottom line: If you want to be sure ChatGPT sticks-to-the-facts when auto-writing your emails and other text, there’s a prompt you can use that eliminates such hallucinations. For the prompt, simply check-out the free sample read of “Auto Writing World-Class Emails With ChatGPT,” by Joe Dysart, available on Amazon. Once you’re on the Amazon book page, click the free sample read button, scroll to Chapter 6 and grab the free prompt there that deep-sixes hallucinations. In other news and analysis on AI writing: *Mark Zuckerberg Releases ChatGPT-Competitor: Facebook inventor Mark Zuckerberg has released a direct competitor to ChatGPT, dubbed ‘Meta AI.’ While Zuckerberg – CEO of Facebook parent company Meta – has already infused many of his company’s apps with artificial intelligence, this is the first time he’s going in a head-to-head competition against today’s major chatbot competitors with a stand-alone AI chatbot. Designed with the look and...

August 5, 2020 Vasilis Vryniotis . No comments The Datumbox Framework v0.8.2 has been released! Download it now from GitHub or Maven Central Repository. What is new? The version 0.8.2 is a limited incremental release that focuses on resolving bugs and updating the dependencies of the framework. Here are the details: Bug Fixes: Resolved an issue on ShapiroWilk which led to the incorrect estimation of the p-value. Dependencies: Java: The framework is now compiled with Java 11. Build Plugins: Updated Maven Compiler, Maven Javadoc, Maven Source, Maven JAR and Surefire to the latest stable version. Libraries: Updated Commons CSV, SLF4J, LIBSVM and JUnit to the latest stable official versions. You can now find on GitHub the code of Datumbox Framework v0.8.2, the updated Code Examples and the pre-trained Machine Learning models of Datumbox Zoo. I am looking forward to your comments and feedback.

This article discusses what an AI strategy means, the different types of AI strategies that you should know about, and how as a leader you can get started with an AI strategy. What Is An AI strategy? An AI strategy may seem like a complicated business-speak, but it’s simply a vision or high-level plan for integrating AI into the organization, such that it aligns with your broader business and automation goals. This high-level plan can be a: Product-level AI strategy (I often call this AI product strategy) Business-unit-level AI strategy Organizational-level AI strategy AI startup strategy The granularity of the plan is often inversely proportional to the magnitude of the vision. So, the bigger the vision, the broader the objectives until each objective is broken down into a roadmap for implementation. Why Do Businesses Need an AI Strategy? So now the question becomes, why does an organization need an AI strategy? Why can’t you just dive into implementation or make an off-the-shelf purchase with little planning? As Dale Carnegie says, “An hour of planning can save you 10 hours of doing” and with AI it can save you much more than that. It can save you months in setbacks and unnecessary...

Tech teams are entering a new era. What used to work in traditional software environments is no longer enough when artificial intelligence becomes central to business operations. The pace, complexity, and collaborative demands of AI are forcing companies to rethink how their teams are built and how they work. Unlike static codebases or predictable workflows, AI systems evolve through data, experimentation, and constant iteration. This requires more than just adding a few machine learning engineers. It calls for tech teams that are agile, cross-functional, and capable of working in sync with both AI systems and business objectives. Companies that get this right are already seeing the benefits. Those that don’t risk turning AI from an opportunity into a bottleneck. We explore how forward-thinking leaders can adapt team dynamics to fully unlock the value of AI. Want guidance from an AI expert on how to implement AI in your business? Contact Fusemachines today! The New Requirements of AI-Driven Tech Teams The shift toward AI-first operations is not just a technological change, it’s an organizational reconfiguration. AI-driven teams must be engineered to support iterative learning, continuous model adaptation, and tight feedback loops between data, infrastructure, and end-users. Key Technical Competencies Now Required...

SUMMARY: Target-based Grid Control Off-center 3rd Person Camera Paint Gun Undo-Redo Improved Visuals for Partial Copy/Paste Jetpack 2.0 …and much more! Hello, Engineers! Vertical Slice 1.2 is here and it brings another round of improvements to Space Engineers 2. This update introduces target-based ship controls, undo/redo for the paint gun, improved visuals for partial copy/paste, and an important improvement of jetpack boost mode. You’ll also find the new off-center third-person camera that gives you clearer visibility by keeping your character’s head to the side, so it doesn’t block your crosshair and target view. For ships, a similar vertical offset keeps your view unobstructed. And as always – there’s plenty more under the hood. Let’s take a look! Vertical Slice 1.2 Features Off-center 3rd Person Camera The new off-center third-person camera gives you better visibility and more control when piloting ships or moving on foot. By default, the camera is set to the right side, but you can cycle between right, center, and left using ALT+V. We’ve also lowered the minimum camera distance, making it easier to see in tight spaces without switching to first-person. Target-based Grid Control We’ve added target-based grid control to make flying ships feel more responsive...