Sriya.AI

Happy to announce that Dr Aditya Kumar, Associate Professor at Missouri University of Science and Technology has joined Sriya.ai as Advisor. We are honored to have him join us

I am happy to inform that Aaron French has joined Sriya.AI as an Advisor. He will advise us around GTM, Business Strategy among other areas. Sriya is proud to welcome Aaron

Happy and proud to announce that Suman Das; Prof of Advanced Manufacturing GA TECH and Founder-CEO of DDM Systems has joined Sriya.AI's Board of Scientific Advisors. We are very excited to have Suman join our team. Thanks Suman for accepting our invite. Srinivas Kilambi CEO Sriya.AI

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Coastal Inundation Prediction We just completed a “Paid POC” on Charleston Area, SC Coastal Inundation datasets. ? We handled 6-7 disparate datasets namely 3 rivers, tide, weather, lunar cycle etc and was able to combine them into 1 master dataset and was able to forecast “Coastal Flooding” in Charleston Area, SC area daily till 2045. ? We also were able to successfully predict with?99% accuracy past 3-5 years coastal flooding?and were able to show actionable insights which when implemented can reduce coastal flooding by 20%. ? We are now looking to expand the model and its predictions along US East coast and especially in GA/FL areas. ? We are meeting our project sponsor today on zoom and with?https://www.noaa.gov/?representative this Thursday for initial discussion on a collaboration.

I am very excited to announce that Sriya.AI has developed and tested world's 1st "Heterogenous Large Numerical Model (HeLNM)". HeLNM is where multiple adjoining datasets are merged to create a master dataset which contains more meaning, information and training than each individual data set. For example: The effect of weather on mining and the combined effect of weather and mining on electricity consumption. Alternately, effect of weather of electricity generation and the combined effect on silica impurity concentration in mining. HeLNMs differ from HoLNMs or homogenous LNM where datasets of same or similar domain or types are merged. We tested a pre-trained model on just mining; mining + weather; mining + electric; mining + weather + electric datasets and saw 86 - 99.9% prediction accuracies and precision on the 2 target features being first predicted and then improved namely: 1. Reduction in silica impurity concentration 2. Reduction in electricity consumption. PFA the results.

Sriya.AI now can even do "Heterogenous Large Numerical Models". This is a Big breakthrough and also can run on a #CPU not a #GPU. PFA our latest research where we have beaten Chat GPT 4.o and H20 AI-ML 10/10 or 100% in all different case studies/verticals. We were the only tech which was able to even get quantified improvements in business outcomes based on actionable insights. This is ROI in AI which is the PAIN for every implementation. We also run on CPUs not GPUs. We are now even able to integrate disparate data like weather forecasts with sales with electricity consumption with mining production and make very accurate predictions using “Heterogenous Large Numerical Models”.

Good Day Friends and AI Global Enthusiasts: This week, I am now coming up with even bigger news. Sriya.AI has now run a comparison test with ChatGPT's 4.o LLM and H2O.ai version: 3.46.0.4 models as well as an updated test Alteryx on 12 different public available datasets in diverse fields like 1. Healthcare 2. Manufacturing 3. SCM 4. Financials 5. HR 6. Marketing 7. Cement R&D Guess what, Sriya.AI's LNM powered by SXI++ was more accurate than both a LLM based tool and a traditional ML based tool in 12/12 cases = 100%. Results are attached below (Alteryx data not reflected). I am proud of what my small company and a team of 10 people have accomplished in the last 1 year. **Note: One of Sriya.AI's major differentiators is its simplicity and how it can run, generate, predict and even improve business outcomes from large numerical data on #CPUs not #GPUs. Yes, you are NOT Hallucinating now ??, Sriya.AI's #LNM runs on dumb old Intel I5-I7 CPU chips and does not need energy guzzling expensive GPUs. I even gave the 3 reasons why and how it is able to run on CPUs vs GPU. The links to those 2 articles are attached here. https://lnkd.in/e5qCE2Sk https://lnkd.in/eFv9xuns Contact [email protected] for additional details and a demo.

Good Day Friends and AI Global Enthusiasts: This week, I am now coming up with even bigger news. Sriya.AI has now run a comparison test with ChatGPT's 4.o LLM and H2O.ai version: 3.46.0.4 models as well as an updated test Alteryx on 12 different public available datasets in diverse fields like 1. Healthcare 2. Manufacturing 3. SCM 4. Financials 5. HR 6. Marketing 7. Cement R&D Guess what, Sriya.AI's LNM powered by SXI++ was more accurate than both a LLM based tool and a traditional ML based tool in 12/12 cases = 100%. Results are attached below (Alteryx data not reflected). I am proud of what my small company and a team of 10 people have accomplished in the last 1 year. **Note: One of Sriya.AI's major differentiators is its simplicity and how it can run, generate, predict and even improve business outcomes from large numerical data on #CPUs not #GPUs. Yes, you are NOT Hallucinating now ??, Sriya.AI's #LNM runs on dumb old Intel I5-I7 CPU chips and does not need energy guzzling expensive GPUs. I even gave the 3 reasons why and how it is able to run on CPUs vs GPU. The links to those 2 articles are attached here. https://lnkd.in/e5qCE2Sk https://lnkd.in/eFv9xuns Contact [email protected] for additional details and a demo.

We compared Sriya LNM with Chat GPT ML LLM. LNM outperformed in 4 out 4. We will share details by Thursday