S Technologies AI pushes boundaries in neural intelligence, language models, and cognitive research — enter our innovation ecosystem.
We build minds, not just models
Every architecture we train starts from the same question the brain answers cheaply and a machine does not: what in this input actually matters? Our work is attention, memory, and representation — and the systems that come out of it.
Transformer architectures trained from scratch, not fine-tuned wrappers.
Representation learning on low-resource languages, Bengali first.
Interpretability built in, so a prediction can be argued with.
Research with something to show for it
At S Technologies AI, we build intelligent systems designed to revolutionize human interaction with technology. From neural network research to generative models, our AI innovations are grounded in ethics, efficiency, and open-source collaboration.
Neural Intelligence
We focus on transformer models and biologically inspired neural nets to mimic human learning and reasoning.
Ethical AI
Our research aligns with global ethical frameworks to ensure safety, transparency, and fairness in AI.
Open Innovation
We embrace collaboration, open data, and community contributions to accelerate scientific progress.
A sentence, one layer at a time
A prompt is split into tokens, carried through a stack of transformer blocks, and turned back into words. Nothing here is magic — it is arithmetic, repeated enough times to be surprising.
Prompt
Transformer stack
Generation
Every word weighed against every other
The matrix below is what replaced recurrence: instead of reading a sentence left to right, the model scores each token against all the others at once and decides where to look. Brighter is heavier.
Query tokens
Key tokens · 8×8
Latest AI Models
DocLM
A brain-inspired transformer model for solving medical science problems.
Fishy
A transformer-based generative model trained with Fisheries datasets.
The numbers behind the work
Figures describing the largest model trained here to date, and the span of the programme around it.
Parameters
Largest model trained in house
Training tokens
Curated, cleaned, and deduplicated
Models released
DocLM, Fishy, Britto AI
Languages modelled
Bengali and English
Researching since
The first team was formed in 2023
What we build on
The libraries, runtimes, and infrastructure our training and serving pipelines are made of.
Training, serving, and everything between
- PyTorch
- TensorFlow
- Keras
- JAX
- Hugging Face
- Transformers
- CUDA
- cuDNN
- NumPy
- pandas
- scikit-learn
- spaCy
- NLTK
- OpenCV
- ONNX
- TensorRT
- FastAPI
- Next.js
- Docker
- Kubernetes
- Redis
- PostgreSQL
- MongoDB
- Vercel
AI Research Highlights
Where each model came from and when it arrived.
DocLM
August 2024
A brain-inspired transformer model for solving medical science problems.
Fishy
December 2023
A transformer-based generative model trained with Fisheries datasets.
Britto AI
November 2023
General-purpose LLM core with few-shot capabilities.
Loss goes down, slowly, for weeks
A training run is not a demo. It is a long argument with a dataset, and the only honest measure of progress is a curve that keeps falling after the easy gains are gone.
Illustrative training curve — shaped for this figure, not a benchmark result
Training is a walk down a surface you cannot see
Every parameter is an axis, and the loss over all of them is a landscape with millions of dimensions. Here are two, so it fits on a screen. Three runs start in different places and walk downhill — and one of them does not reach the bottom.
- Run 1 — convergedRolls off the ridge and settles in the global minimum.
- Run 2 — convergedA different initialisation, the same destination. This is what you hope for.
- Run 3 — local minimumFalls into the nearer basin and stops. Nothing about the loss tells it there is a deeper one two ridges over — which is why initialisation, momentum and learning rate are not details.
Where the model looks while it writes Bengali
English puts the verb in the middle and Bengali puts it at the end, so a translation cannot be produced word by word in order. Watch the link carrying "reads" cross every other one on its way to the last position — that crossing is the grammar being handled.
Source — English
আমাদেরমডেলবাংলাসরাসরিপড়েGenerated — Bengali
What the models learn, and where it goes
Training turns a pile of documents into a geometry: things that mean similar things end up near each other. Each of our three models carves out its own region of that space — and that is what makes them useful in the fields below.
AI in Healthcare
From early diagnosis to drug discovery, AI is revolutionizing the medical field with data-driven predictions and personalized treatment.
AI in Climate Science
Predicting extreme weather, mapping ocean health, and optimizing renewable energy — AI enables a sustainable planet.
AI in Security and Ethics
We develop models with responsible AI protocols, ensuring bias mitigation, privacy preservation, and ethical decision-making.
Everything in orbit around one team
The models, the tools they are served with, and the open-source projects they were built on top of.
Latest News
Unpublished
DocLM
DocLM is a transformer-based generative AI model for the medical science industry.
November 14, 2024
Fishy
Fishy is a transformer-based generative AI model for the fisheries industry.
Unpublished
Britto AI
Britto AI is our most advanced LLM for general tasks.
June 16, 2016
Launched S Technologies Research Center
S Technologies launched it's dedicated center for research to work for AI and software technologies.
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