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Augmented Reality Entertainment: Real-Time Digital Fun

Augmented Reality Entertainment: Real-Time Digital Fun

28/03/2025

See how augmented reality entertainment is changing film, gaming, and live events with digital elements, AR apps, and real-time interactive experiences.
Why do we need GPU in AI?

Why do we need GPU in AI?

16/07/2024

Discover why GPUs are essential in AI. Learn about their role in machine learning, neural networks, and deep learning projects.
How to use GPU Programming in Machine Learning?

How to use GPU Programming in Machine Learning?

9/07/2024

Learn how to implement and optimise machine learning models using NVIDIA GPUs, CUDA programming, and more. Find out how TechnoLynx can help you adopt this technology effectively.
Retrieval Augmented Generation (RAG): Examples and Guidance

Retrieval Augmented Generation (RAG): Examples and Guidance

23/04/2024

Learn about Retrieval Augmented Generation (RAG), a powerful approach in natural language processing that combines information retrieval and generative AI.
Computer Vision for Quality Control

Computer Vision for Quality Control

16/11/2023

Let's talk about how artificial intelligence, coupled with computer vision, is reshaping manufacturing processes!

Articles

Cost, Efficiency, and Value Are Not the Same Metric

Cost, Efficiency, and Value Are Not the Same Metric

17/04/2026

Performance per dollar. Tokens per watt. Cost per request. These sound like the same thing said differently, but they measure genuinely different dimensions of AI infrastructure economics. Conflating them leads to infrastructure decisions that optimize for the wrong objective.
Precision Is an Economic Lever in Inference Systems

Precision Is an Economic Lever in Inference Systems

17/04/2026

Precision isn't just a numerical setting — it's an economic one. Choosing FP8 over BF16, or INT8 over FP16, changes throughput, latency, memory footprint, and power draw simultaneously. For inference at scale, these changes compound into significant cost differences.
Precision Choices Are Constrained by Hardware Architecture

Precision Choices Are Constrained by Hardware Architecture

17/04/2026

You can't run FP8 inference on hardware that doesn't have FP8 tensor cores. Precision format decisions are conditional on the accelerator's architecture — its tensor core generation, native format support, and the efficiency penalties for unsupported formats.
Steady-State Performance, Cost, and Capacity Planning

Steady-State Performance, Cost, and Capacity Planning

17/04/2026

Capacity planning built on peak performance numbers over-provisions or under-delivers. Real infrastructure sizing requires steady-state throughput — the predictable, sustained output the system actually delivers over hours and days, not the number it hit in the first five minutes.
How Benchmark Context Gets Lost in Procurement

How Benchmark Context Gets Lost in Procurement

16/04/2026

A benchmark result starts with full context — workload, software stack, measurement conditions. By the time it reaches a procurement deck, all that context is gone. The failure mode is not wrong benchmarks but context loss during propagation.
Building an Audit Trail: Benchmarks as Evidence for Governance and Risk

Building an Audit Trail: Benchmarks as Evidence for Governance and Risk

16/04/2026

High-value AI hardware decisions need traceable evidence, not slide-deck bullet points. When benchmarks are documented with methodology, assumptions, and limitations, they become auditable institutional evidence — defensible under scrutiny and revisitable when conditions change.
The Comparability Protocol: Why Benchmark Methodology Defines What You Can Compare

The Comparability Protocol: Why Benchmark Methodology Defines What You Can Compare

16/04/2026

Two benchmark scores can only be compared if they share a declared methodology — the same workload, precision, measurement protocol, and reporting conditions. Without that contract, the comparison is arithmetic on numbers of unknown provenance.
A Decision Framework for Choosing AI Hardware

A Decision Framework for Choosing AI Hardware

16/04/2026

Hardware selection is a multivariate decision under uncertainty — not a score comparison. This framework walks through the steps: defining the decision, matching evaluation to deployment, measuring what predicts production, preserving tradeoffs, and building a repeatable process.
How Benchmarks Shape Organizations Before Anyone Reads the Score

How Benchmarks Shape Organizations Before Anyone Reads the Score

16/04/2026

Before a benchmark score informs a purchase, it has already shaped what gets optimized, what gets reported, and what the organization considers important. Benchmarks function as decision infrastructure — and that influence deserves more scrutiny than the number itself.
Accuracy Loss from Lower Precision Is Task‑Dependent

Accuracy Loss from Lower Precision Is Task‑Dependent

16/04/2026

Reduced precision does not produce a uniform accuracy penalty. Sensitivity depends on the task, the metric, and the evaluation setup — and accuracy impact cannot be assumed without measurement.

Latest Posts

16/04/2026

Precision Is a Design Parameter, Not a Quality Compromise

16/04/2026

Mixed Precision Works by Exploiting Numerical Tolerance

16/04/2026

Throughput vs Latency: Choosing the Wrong Optimization Target

16/04/2026

Quantization Is Controlled Approximation, Not Model Damage

15/04/2026

GPU Utilization Is Not Performance

15/04/2026

FP8, FP16, and BF16 Represent Different Operating Regimes

15/04/2026

Peak Performance vs Steady‑State Performance in AI

15/04/2026

The Software Stack Is a First‑Class Performance Component

15/04/2026

The Mythology of 100% GPU Utilization

15/04/2026

Why Benchmarks Fail to Match Real AI Workloads

15/04/2026

Why Identical GPUs Often Perform Differently

15/04/2026

Training and Inference Are Fundamentally Different Workloads

15/04/2026

Performance Ownership Spans Hardware and Software Teams

15/04/2026

Performance Emerges from the Hardware × Software Stack

14/04/2026

Power, Thermals, and the Hidden Governors of Performance

14/04/2026

Why AI Performance Changes Over Time

14/04/2026

CUDA, Frameworks, and Ecosystem Lock-In

14/04/2026

GPUs Are Part of a Larger System

14/04/2026

Why AI Performance Must Be Measured Under Representative Workloads

14/04/2026

Low GPU Utilization: Where the Real Bottlenecks Hide

14/04/2026

Why GPU Performance Is Not a Single Number

14/04/2026

What a GPU Benchmark Actually Measures

14/04/2026

Why Spec‑Sheet Benchmarking Fails for AI

19/03/2026

NVIDIA Data Centre GPUs: what they are and why they matter

16/03/2026

CUDA vs OpenCL: Which to Use for GPU Programming
Planning GPU Memory for Deep Learning Training

Planning GPU Memory for Deep Learning Training

16/02/2026

GPU memory estimation for deep learning: calculating weight, activation, and gradient buffers so you can predict whether a training run fits before it crashes.
CUDA AI for the Era of AI Reasoning

CUDA AI for the Era of AI Reasoning

11/02/2026

How CUDA underpins AI inference: kernel execution, memory hierarchy, and the software decisions that determine whether a model uses the GPU efficiently or wastes it.
Choosing Vulkan, OpenCL, SYCL or CUDA for GPU Compute

Choosing Vulkan, OpenCL, SYCL or CUDA for GPU Compute

28/01/2026

A practical comparison of Vulkan, OpenCL, SYCL and CUDA, covering portability, performance, tooling, and how to pick the right path for GPU compute across different hardware vendors.
Deep Learning Models for Accurate Object Size Classification

Deep Learning Models for Accurate Object Size Classification

27/01/2026

A clear and practical guide to deep learning models for object size classification, covering feature extraction, model architectures, detection pipelines, and real‑world considerations.
GPU vs TPU vs CPU: Performance and Efficiency Explained

GPU vs TPU vs CPU: Performance and Efficiency Explained

10/01/2026

CPU, GPU, and TPU compared for AI workloads: architecture differences, energy trade-offs, practical pros and cons, and a decision framework for choosing the right accelerator.
GPU Computing for Faster Drug Discovery

GPU Computing for Faster Drug Discovery

7/01/2026

GPU computing in drug discovery: how parallel workloads accelerate molecular simulation, docking calculations, and deep learning models for compound property prediction.
The Role of GPU in Healthcare Applications

The Role of GPU in Healthcare Applications

6/01/2026

Where GPUs are essential in healthcare AI: medical image processing, genomic workloads, and real-time inference that CPU-only architectures cannot sustain at production scale.
AI Transforming the Future of Biotech Research

AI Transforming the Future of Biotech Research

16/12/2025

AI in biotech research: how machine learning accelerates compound screening, genomic analysis, and experimental design decisions in biological research pipelines.
AI and Data Analytics in Pharma Innovation

AI and Data Analytics in Pharma Innovation

15/12/2025

Machine learning in pharma: applying biomarker analysis, adverse event prediction, and data pipelines to regulated pharmaceutical research and development workflows.
AI in Rare Disease Diagnosis and Treatment

AI in Rare Disease Diagnosis and Treatment

12/12/2025

AI for rare disease diagnosis: how small dataset constraints shape model selection, transfer learning strategies, and the clinical validation requirements.
Mimicking Human Vision: Rethinking Computer Vision Systems

Mimicking Human Vision: Rethinking Computer Vision Systems

10/11/2025

Why computer vision systems trained on benchmarks fail on real inputs, and how attention mechanisms, context modelling, and multi-scale features close the gap.
Visual analytic intelligence of neural networks

Visual analytic intelligence of neural networks

7/11/2025

Neural network visualisation: how activation maps, layer inspection, and feature attribution reveal what a model has learned and where it will fail.
Visual Computing in Life Sciences: Real-Time Insights

Visual Computing in Life Sciences: Real-Time Insights

6/11/2025

Learn how visual computing transforms life sciences with real-time analysis, improving research, diagnostics, and decision-making for faster, accurate outcomes.
AI-Driven Aseptic Operations: Eliminating Contamination

AI-Driven Aseptic Operations: Eliminating Contamination

21/10/2025

Learn how AI-driven aseptic operations help pharmaceutical manufacturers reduce contamination, improve risk assessment, and meet FDA standards for safe, sterile products.
AI Visual Quality Control: Assuring Safe Pharma Packaging

AI Visual Quality Control: Assuring Safe Pharma Packaging

20/10/2025

See how AI-powered visual quality control ensures safe, compliant, and high-quality pharmaceutical packaging across a wide range of products.
AI for Reliable and Efficient Pharmaceutical Manufacturing

AI for Reliable and Efficient Pharmaceutical Manufacturing

15/10/2025

See how AI and generative AI help pharmaceutical companies optimise manufacturing processes, improve product quality, and ensure safety and efficacy.
Barcodes in Pharma: From DSCSA to FMD in Practice

Barcodes in Pharma: From DSCSA to FMD in Practice

25/09/2025

What the 2‑D barcode and seal on your medicine mean, how pharmacists scan packs, and why these checks stop fake medicines reaching you.
Pharma’s EU AI Act Playbook: GxP‑Ready Steps

Pharma’s EU AI Act Playbook: GxP‑Ready Steps

24/09/2025

A clear, GxP‑ready guide to the EU AI Act for pharma and medical devices: risk tiers, GPAI, codes of practice, governance, and audit‑ready execution.
Cell Painting: Fixing Batch Effects for Reliable HCS

Cell Painting: Fixing Batch Effects for Reliable HCS

23/09/2025

Reduce batch effects in Cell Painting. Standardise assays, adopt OME‑Zarr, and apply robust harmonisation to make high‑content screening reproducible.
Explainable Digital Pathology: QC that Scales

Explainable Digital Pathology: QC that Scales

22/09/2025

Raise slide quality and trust in AI for digital pathology with robust WSI validation, automated QC, and explainable outputs that fit clinical workflows.
Validation‑Ready AI for GxP Operations in Pharma

Validation‑Ready AI for GxP Operations in Pharma

19/09/2025

Make AI systems validation‑ready across GxP. GMP, GCP and GLP. Build secure, audit‑ready workflows for data integrity, manufacturing and clinical trials.
Edge Imaging for Reliable Cell and Gene Therapy

Edge Imaging for Reliable Cell and Gene Therapy

17/09/2025

Edge imaging transforms cell & gene therapy manufacturing with real‑time monitoring, risk‑based control and Annex 1 compliance for safer, faster production.
AI in Genetic Variant Interpretation: From Data to Meaning

AI in Genetic Variant Interpretation: From Data to Meaning

15/09/2025

AI enhances genetic variant interpretation by analysing DNA sequences, de novo variants, and complex patterns in the human genome for clinical precision.
AI Visual Inspection for Sterile Injectables

AI Visual Inspection for Sterile Injectables

11/09/2025

Improve quality and safety in sterile injectable manufacturing with AI‑driven visual inspection, real‑time control and cost‑effective compliance.
Predicting Clinical Trial Risks with AI in Real Time

Predicting Clinical Trial Risks with AI in Real Time

5/09/2025

AI helps pharma teams predict clinical trial risks, side effects, and deviations in real time, improving decisions and protecting human subjects.
Generative AI in Pharma: Compliance and Innovation

Generative AI in Pharma: Compliance and Innovation

1/09/2025

Generative AI transforms pharma by streamlining compliance, drug discovery, and documentation with AI models, GANs, and synthetic training data for safer innovation.
AI for Pharma Compliance: Smarter Quality, Safer Trials

AI for Pharma Compliance: Smarter Quality, Safer Trials

27/08/2025

AI helps pharma teams improve compliance, reduce risk, and manage quality in clinical trials and manufacturing with real-time insights.
Case Study: CloudRF  Signal Propagation and Tower Optimisation

Case Study: CloudRF  Signal Propagation and Tower Optimisation

15/05/2025

See how TechnoLynx helped CloudRF speed up signal propagation and tower placement simulations with GPU acceleration, custom algorithms, and cross-platform support. Faster, smarter radio frequency planning made simple.
AI Object Tracking Solutions: Intelligent Automation

AI Object Tracking Solutions: Intelligent Automation

12/05/2025

Multi-object tracking in production: handling occlusion, re-identification, and real-time latency constraints in industrial and retail camera systems.
Automating Assembly Lines with Computer Vision

Automating Assembly Lines with Computer Vision

24/04/2025

Integrating computer vision into assembly lines: inspection system design, detection accuracy targets, and edge deployment considerations for manufacturing environments.
The Growing Need for Video Pipeline Optimisation

The Growing Need for Video Pipeline Optimisation

10/04/2025

Video pipeline optimisation: how encoding, transmission, and decoding decisions determine real-time computer vision latency and processing throughput at scale.
Unlocking XR’s True Power with Smarter GPU Optimisation

Unlocking XR’s True Power with Smarter GPU Optimisation

9/04/2025

GPU optimisation for real-time rendering workloads: profiling GPU-bound bottlenecks, memory bandwidth constraints, and frame scheduling decisions in XR systems.
Markov Chains in Generative AI Explained

Markov Chains in Generative AI Explained

31/03/2025

Discover how Markov chains power Generative AI models, from text generation to computer vision and AR/VR/XR. Explore real-world applications!
Smarter and More Accurate AI: Why Businesses Turn to HITL

Smarter and More Accurate AI: Why Businesses Turn to HITL

27/03/2025

Human-in-the-loop AI: how to design review queues that maintain throughput while keeping humans in control of low-confidence and edge-case decisions.
Optimising Quality Control Workflows with AI and Computer Vision

Optimising Quality Control Workflows with AI and Computer Vision

24/03/2025

Quality control with computer vision: inspection pipeline design, defect detection architectures, and the measurement factors that determine false-reject rates in production.
Inventory Management Applications: Computer Vision to the Rescue!

Inventory Management Applications: Computer Vision to the Rescue!

17/03/2025

Computer vision for inventory counting and tracking: how shelf-state monitoring, object detection, and anomaly detection reduce manual audit overhead in warehouses and retail.
Explainability (XAI) In Computer Vision

Explainability (XAI) In Computer Vision

17/03/2025

Explainability in computer vision: how saliency maps, attention visualisation, and interpretable architectures make CV models auditable and correctable in production.
The Impact of Computer Vision on Real-Time Face Detection

The Impact of Computer Vision on Real-Time Face Detection

10/02/2025

Real-time face detection in production: CNN architecture choices, detection pipeline design, and the latency constraints that determine deployment feasibility.
Optimising LLMOps: Improvement Beyond Limits!

Optimising LLMOps: Improvement Beyond Limits!

2/01/2025

LLMOps optimisation: profiling throughput and latency bottlenecks in LLM serving systems and the infrastructure decisions that determine sustainable performance under load.
MLOps for Hospitals - Staff Tracking (Part 2)

MLOps for Hospitals - Staff Tracking (Part 2)

9/12/2024

Hospital staff tracking system, Part 2: training the computer vision model, containerising for deployment, setting inference latency targets, and configuring production monitoring.
MLOps for Hospitals - Building a Robust Staff Tracking System (Part 1)

MLOps for Hospitals - Building a Robust Staff Tracking System (Part 1)

2/12/2024

Building a hospital staff tracking system with computer vision, Part 1: sensor setup, data collection pipeline, and the MLOps environment for training and iteration.
MLOps vs LLMOps: Let’s simplify things

MLOps vs LLMOps: Let’s simplify things

25/11/2024

MLOps and LLMOps compared: why LLM deployment requires different tooling for prompt management, evaluation pipelines, and model drift than classical ML workflows.
Streamlining Sorting and Counting Processes with AI

Streamlining Sorting and Counting Processes with AI

19/11/2024

Learn how AI aids in sorting and counting with applications in various industries. Get hands-on with code examples for sorting and counting apples based on size and ripeness using instance segmentation and YOLO-World object detection.
Maximising Efficiency with AI Acceleration

Maximising Efficiency with AI Acceleration

21/10/2024

Find out how AI acceleration is transforming industries. Learn about the benefits of software and hardware accelerators and the importance of GPUs, TPUs, FPGAs, and ASICs.
Enhance Your Applications with Promising GPU APIs

Enhance Your Applications with Promising GPU APIs

16/08/2024

CUDA, OpenCL, Metal, and Vulkan compared for GPU compute: when to use each API and what the trade-offs are for different application targets and hardware platforms.
AI in Pharmaceutics: Automating Meds

AI in Pharmaceutics: Automating Meds

28/06/2024

Artificial intelligence is without a doubt a big deal when included in our arsenal in many branches and fields of life sciences, such as neurology, psychology, and diagnostics and screening. In this article, we will see how AI can also be beneficial in the field of pharmaceutics for both pharmacists and consumers. If you want to find out more, keep reading!
Exploring Diffusion Networks

Exploring Diffusion Networks

10/06/2024

Diffusion networks explained: the forward noising process, the learned reverse pass, and how these models are trained and used for image generation.
The AI Innovations Behind Smart Retail

The AI Innovations Behind Smart Retail

6/05/2024

How computer vision powers shelf monitoring, customer flow analysis, and checkout automation in retail environments — and what integration actually requires.
The Synergy of AI: Screening & Diagnostics on Steroids!

The Synergy of AI: Screening & Diagnostics on Steroids!

3/05/2024

Computer vision in medical imaging: how AI systems accelerate screening and diagnostic workflows while managing the false-positive rates that determine clinical acceptance.
A Gentle Introduction to CoreMLtools

A Gentle Introduction to CoreMLtools

18/04/2024

CoreML and coremltools explained: how to convert trained models to Apple's on-device format and deploy computer vision models in iOS and macOS applications.
Introduction to MLOps

Introduction to MLOps

4/04/2024

What MLOps is, why organisations fail to move models from training to production, and the tooling and processes that close the gap between experimentation and deployed systems.
Case-Study: Text-to-Speech Inference Optimisation on Edge (Under NDA)

Case-Study: Text-to-Speech Inference Optimisation on Edge (Under NDA)

12/03/2024

See how our team applied a case study approach to build a real-time Kazakh text-to-speech solution using ONNX, deep learning, and different optimisation methods.
Case-Study: V-Nova - GPU Porting from OpenCL to Metal

Case-Study: V-Nova - GPU Porting from OpenCL to Metal

15/12/2023

Case study on moving a GPU application from OpenCL to Metal for our client V-Nova. Boosts performance, adds support for real-time apps, VR, and machine learning on Apple M1/M2 chips.
Computer Vision in Manufacturing

Computer Vision in Manufacturing

19/10/2023

Computer vision in manufacturing: how inspection systems detect defects, verify assembly, and measure dimensional tolerances in real-time production environments.
Generating New Faces

Generating New Faces

6/10/2023

With the hype of generative AI, all of us had the urge to build a generative AI application or even needed to integrate it into a web application.
AI in drug discovery

AI in drug discovery

22/06/2023

A new groundbreaking model developed by researchers at the MIT utilizes machine learning and AI to accelerate the drug discovery process.
Case-Study: Generative AI for Stock Market Prediction

Case-Study: Generative AI for Stock Market Prediction

6/06/2023

Case study on using Generative AI for stock market prediction. Combines sentiment analysis, natural language processing, and large language models to identify trading opportunities in real time.
Case-Study: Performance Modelling of AI Inference on GPUs

Case-Study: Performance Modelling of AI Inference on GPUs

15/05/2023

Learn how TechnoLynx helps reduce inference costs for trained neural networks and real-time applications including natural language processing, video games, and large language models.
3 Ways How AI-as-a-Service Burns You Bad

3 Ways How AI-as-a-Service Burns You Bad

4/05/2023

Listen what our CEO has to say about the limitations of AI-as-a-Service.
Generative models in drug discovery

Generative models in drug discovery

26/04/2023

Traditionally, drug discovery is a slow and expensive process that involves trial and error experimentation.
Case Study: Multi-Target Multi-Camera Tracking

Case Study: Multi-Target Multi-Camera Tracking

10/02/2023

Learn how TechnoLynx built a cost-efficient, AI-powered multi-target tracking system using existing CCTV infrastructure. Real-time object tracking across non-overlapping cameras using global and local IDs.
The three Reasons Why GPUs Didnt Work Out for You

The three Reasons Why GPUs Didnt Work Out for You

1/02/2023

Most GPU-naïve companies would like to think of GPUs as CPUs with many more cores and wider SIMD lanes, but unfortunately, that understanding is missing some crucial differences.
Case-Study: Action Recognition for Security (Under NDA)

Case-Study: Action Recognition for Security (Under NDA)

11/01/2023

See how TechnoLynx used AI-powered action recognition to improve video analysis and automate complex tasks. Learn how smart solutions can boost efficiency and accuracy in real-world applications.
Training a Language Model on a Single GPU in one day

Training a Language Model on a Single GPU in one day

4/01/2023

AI Research from the University of Maryland investigating the cramming challenge for Training a Language Model on a Single GPU in one day.
Case-Study: V-Nova - Metal-Based Pixel Processing for Video Decoder

Case-Study: V-Nova - Metal-Based Pixel Processing for Video Decoder

15/12/2022

TechnoLynx improved V-Nova’s video decoder with GPU-based pixel processing, Metal shaders, and efficient image handling for high-quality colour images across Apple devices.
Consulting: AI for Personal Training Case Study - Kineon

Consulting: AI for Personal Training Case Study - Kineon

2/11/2022

TechnoLynx partnered with Kineon to design an AI-powered personal training concept, combining biosensors, machine learning, and personalised workouts to support fitness goals and personal training certification paths.
Case-Study: A Generative Approach to Anomaly Detection (Under NDA)

Case-Study: A Generative Approach to Anomaly Detection (Under NDA)

22/05/2022

See how we successfully compeleted this project using Anomaly Detection!
Case Study: Accelerating Cryptocurrency Mining (Under NDA)

Case Study: Accelerating Cryptocurrency Mining (Under NDA)

29/12/2020

Our client had a vision to analyse and engage with the most disruptive ideas in the crypto-currency domain. Read more to see our solution for this mission!
Case Study - AI-Generated Dental Simulation

Case Study - AI-Generated Dental Simulation

10/11/2020

Our client, Tasty Tech, was an organically growing start-up with a first-generation product in the dental space, and their product-market fit was validated. Read more.
Case Study - Fraud Detector Audit (Under NDA)

Case Study - Fraud Detector Audit (Under NDA)

17/09/2020

Discover how a robust fraud detection system combines traditional methods with advanced machine learning to detect various forms of fraud!
Case Study - Embedded Video Coding on GPU (Under NDA)

Case Study - Embedded Video Coding on GPU (Under NDA)

15/04/2020

TechnoLynx developed a customised embedded video coding solution using GPU optimisation, dedicated graphics cards, and discrete GPUs to enhance video compression efficiency, performance, and integration within the client’s pipeline.
Case Study - Accelerating Physics -Simulation Using GPUs (Under NDA)

Case Study - Accelerating Physics -Simulation Using GPUs (Under NDA)

23/01/2020

TechnoLynx used GPU acceleration to improve physics simulations for an SME, leveraging dedicated graphics cards, advanced algorithms, and real-time processing to deliver high-performance solutions, opening up new applications and future development potential.