Arivu IQ, Corp

We’re thrilled to announce that InoFii Technologies, AIQ's development partner in India, has officially rebranded to Arivu IQ India! This evolution embodies our relentless commitment to innovation, growth, and our mission to humanize tech solutions. Same Team, Same Purpose, Same Style, Same Amazing Outcomes! Now, our brands feel even more aligned and connected. Arivu IQ India represents our evolving mission to create smarter, more intuitive technology that truly understands and serves the needs of our clients and partners. As we continue on this new chapter, we remain dedicated to transforming the digital space, one step at a time. Thank you to our incredible team, clients, and partners for your continued support and trust. Here’s to new beginnings and achieving greater heights together! In the next few days, we will share our new messaging in line with Arivu IQ Corp. #ArivuIQIndia #Rebranding #Innovation #Technology #DigitalTransformation #NewBeginnings #AIQ #ArivuIQ #AI

Cheers to the vibrant spirit of Tamil New Year! Sending festive greetings and love from the heart of Chennai. #arivuiq #aiq #love #people #festive

Sending warm wishes to all celebrating Eid al-Fitr! May this special occasion bring joy, peace, and prosperity to you and your loved ones. Eid Mubarak! 🌙✨ #EidMubarak #EidAlFitr #Celebration #Joy #Peace #Prosperity

Next-Gen Fusion: Harnessing the Might of LLMs in Traditional Software Frameworks A Dance of Code and Charisma: At its core, traditional software is about executing machine code — a deterministic sequence of instructions. The new kid on the block, LLM (Large Language Models), operates on a seemingly different principle: predicting the next word or sequence. But when we peel back the layers, are they really that different? And, more importantly, how can we integrate these seemingly opposing natures to solve complex problems? Just as software isn’t solely about machine code, LLMs are far more than just word predictors. Software has evolved over the years, developing layers of abstraction like Object-Oriented Programming and high-level language constructs. Similarly, LLMs have moved beyond basic predictions, showing emergent capabilities like instruction-based learning and situational adaptation. Software is grounded in logic and rigid rules. LLMs, on the other hand, display learned behaviors that aren’t always rooted in pure logic and preset rules. Foundations of Software: Rooted in logic and fixed instructions, traditional software is built upon rigid rules. It simply follows a set of instructions in sequence, ensuring the same output given the same input. Take, for instance, the classic “if-then-else” statement in programming. A simple statement if [condition] then [execute action A] else [execute action B] A complex statement (if statement 1) AND/OR (if statement 2) AND/OR (if statement 3) … Although software can handle complexity through nested conditions and parallel decision-making structures, it remains fundamentally rule-based. While this might bring a certain level of adaptability and non-determinism based on input parameters, it doesn’t showcase the kind of emergent behaviors associated with intelligence. More importantly, conventional software sometimes falls short when dealing with multi-objective complexities that align closely with human values, which are inherently nuanced and hard to define logically. Foundations of LLMs: These models, on the other hand, rely on pattern recognition rather than deterministic rules. Think of it like this: instead of being told step-by-step how to dance, an LLM watches countless dancers and naturally picks up the moves that resonate most. This learning process is facilitated by a weighted system. For instance, if more people prefer a particular dance move, that preference acts as a “weight”, prompting the model to prioritize that move over others. Each step doesn’t have a logical right or wrong. Some moves resonate with others and are accepted by the majority. Similarly, LLMs internalize and emulate patterns that are popular and acceptable within the vast swathes of data they are trained on. To understand how to maximize the potential of LLMs you can read more in the article via the below link. https://lnkd.in/ezC58eZF

Wishing you a joyous and prosperous Pongal from ALL OF US at Arivu IQ! May this harvest festival bring abundant blessings, happiness, and prosperity to you and your loved ones. Happy Pongal!

Cheers to the possibilities and opportunities that the New Year brings. May you make the most of every moment and find joy in new journeys. Happy New Year! #AIQ #ArivuIQ #HappyNewYear

Cheers to the possibilities and opportunities that the New Year brings. May you make the most of every moment and find joy in new journeys. Happy New Year! #AIQ #ArivuIQ #HappyNewYear

Sending you love and the joy of shared laughter this Christmas! Happy holidays and a wonderful New Year ahead from all of us at AIQ! Merry Christmas!🎄   #AIQ #ArivuIQ #MerryChristmas

Delighted to have Stephen(Don) Mallik, our Chief AI Officer in the spotlight of CIOLook magazine. A key figure in the team, Mallik strategically shapes the very foundation of humanizing AI technology towards a transformative future. Check out the feature here: https://cutt.ly/NwDfyBZ4 #AIQ #ArivuIQ #ArtificialIntelligence #AI2023 #AItechnology #technology #techbusiness #technologysolutions #AISolutions #BusinessInnovation #ciolook #TechIntegration

Sending you love and the joy of shared laughter this Christmas! Happy holidays and a wonderful New Year ahead from all of us at AIQ! Merry Christmas!🎄   #AIQ #ArivuIQ #MerryChristmas