TurinTech AI+Intel® AI Tools Frameworks: Speed up your ML development and inferencing on CPUs and GPUs


The pace of innovation in artificial intelligence is astounding. From financial forecasting to customer service chatbots, AI now plays a pivotal role across industries. However, developing high-performance AI applications remains difficult and time-consuming. Data scientists and AI developers face immense challenges in understanding advanced software and hardware architectures to maximise AI performance. The data science lifecycle itself tends to be fragmented and slow, taking months from an experimental idea to a production ready AI application. 

To overcome these challenges, TurinTech AI has partnered with Intel to make developing production-ready, high-speed ML models easier than ever. In this article, we will examine the intricacies of building performant AI applications and how TurinTech AI and Intel jointly solve the key pain points. 

Boosting ML Performance is Critical but Challenging 

Slow ML models can lead to issues such as financial loss, customer loss, and technical performance problems. In our previous article, we emphasise why fast ML predictions are crucial in business areas such as high frequency trading, customer service, and devices on the edge of networks. 

The speed and efficiency of AI largely depend on four main areas: data, infrastructure, code, and talents. However, the swift advancement in AI software and hardware poses steep learning curves for data scientists and AI developers. Mastering new optimised libraries, frameworks and hardware architectures demands substantial time and effort. Many data scientists find their skills quickly outdated as companies rapidly adopt the latest innovations. Continuing learning is vital yet difficult alongside full-time roles. Specialisation for diverse hardware like CPUs, GPUs and TPUs also hinders versatility. 

Furthermore, the traditional data science lifecycle, marked by lengthy periods of data preparation, model development, and testing, often extending over weeks or even months, significantly slows down the delivery of AI solutions. This not only hampers the speed of innovation but can also lead to missed opportunities as models risk becoming outdated before deployment. 

All these complexities together make the task of improving ML performance a big challenge. This highlights the need for a streamlined way of developing high-performance machine learning for target hardware. 

TurinTech AI and Intel Join Forces to Speed Up your ML Development and Inferencing 

Intel® AI Tools 

As AI models evolve more rapidly than hardware advancements, significant performance boosts from software AI accelerators become crucial. If hardware acceleration is updating to a bike, software acceleration is upgrading to a supersonic jet. 

Intel’s oneAPI AI Toolsgive data scientists, AI developers, and researchers familiar Python* tools and frameworks to accelerate end-to-end data science and analytics pipelines on Intel® architecture. These Intel optimised ML frameworks and libraries, for example, the Intel® Distribution for Python, Intel® Extension for Scikit-learn, Intel® oneAPI Data Analytics Library, help increase their performance by orders of magnitude on Intel platforms designed to deliver drop-in 10-100X software AI acceleration. 

TurinTech’s evoML platform  

TurinTech’s evoML platform uses GenAI to speed up the process of developing and deploying production-quality ML model code. It automates the end-to-end data science lifecycle, including automatic data pre-processing, hyperparameter tuning, parallel model training, multi-objective optimisation for target hardware, and automatic ML code review and deployment.  

Harnessing GenAI, evoML supercharges data science workflows with advanced capabilities. For example, Synthetic Data Generation augments training data using realistic datasets, ensuring robust model performance, while Intelligent Model Selection suggests optimal machine learning models based on data characteristics, streamlining the ML process for the best results. 

TurinTech AI+ Intel 

TurinTech AI is a proud member of Intel® Partner Alliance. Together, TurinTech’s evoML platform and Intel® AI Tools offer a range of significant benefits for data scientists and AI developers.

  • Accelerated ML Lifecycle: Streamline the end-to-end machine learning process, reducing the time spent on manual data preparation and model training from weeks to days, allowing more time for ideation and experimentation. 
  • GenAI-empowered Data Science: Effortlessly tackle complex data science tasks with GenAI, from synthetic data generation and feature engineering to model selection and explanation, delivering high-performing models in less time. 
  • Seamless Integration: Access Intel’s optimised ML and LLM libraries seamlessly within the evoML platform, eliminating the need to switch between different tools and environments. 
  • Flexibility and Full Control: Tailor the ML workflow to your specific needs with flexible automation options, and gain full control by downloading the source code for further customisation. 
  • Enhanced Performance: Harness the power of Intel hardware (e.g., Intel® Gaudi 3 AI Accelerator) and software optimisations to achieve optimal AI performance, without the need to learn new tools or make significant code changes. 

Now, let’s explore two case studies that demonstrate the performance improvements achieved by leveraging evoML and Intel in different domains. 

Case Study 1: Accelerating Stock Prediction: evoML and Intel® Distribution for Python Achieves Faster Inference and Speedup in Model Training 


Achieving optimal performance for an AI-based stock prediction model is crucial for timely and accurate forecasting. However, the computational demands of such models can be intensive, leading to latency and throughput bottlenecks. 


AI and ML developers in Financial Services can leverage TurinTech AI’s evoML platform to quickly build stock prediction models from their raw data. EvoML seamlessly integrates the Intel® Distribution for Python* and oneAPI AI Tools, allowing you to harness Intel’s powerful hardware capabilities without modifying your code. 

The XGBoost Classifier, a critical component of time series classification model, has been optimised by utilising the Intel®  Python* API (daal4py) for Intel® oneAPI Data Analytics Library (oneDAL) to leverage the capabilities of Intel’s 3rd generation Intel® Xeon® Platinum 8380 CPU. This optimisation ensures that stock prediction model can efficiently utilise the underlying hardware resources. 


  • Hardware acceleration with Intel’s CPU architecture for maximum performance. 
  • Rapid deployment of high-performance AI trading solutions for a competitive edge.

Case Study 2: Supercharging Machine Learning with evoML and Intel® Extension for Scikit-learn: Faster Predictions, Higher Accuracy, Better Precision 


While Scikit-learn offers a wide range of machine learning algorithms and a user-friendly interface, its computational demands can lead to performance bottlenecks, hindering the timeliness of insights and compromising model accuracy. 


Data scientists can leverage the power of TurinTech AI’s evoML platform and Intel’s Extension for Scikit-learn to accelerate your Scikit-learn workflows. This solution allows you to dynamically patch Scikit-learn estimators with mathematically equivalent but accelerated versions, powered by Intel’s AI Tools. By doing so, you can benefit from hardware acceleration on Intel CPUs and GPUs across single-node and multi-node configurations, without modifying your existing code. 

About Intel® AI Tools 

Intel® AI Tools is an open, standards-based programming system designed to simplify development for data-centric workloads across various architectures like CPUs, GPUs, FPGAs, and more. It offers a unified approach, eliminating the need for separate codebases and tools for each architecture. 

About Intel® Partner Alliance 

Intel® Partner Alliance membership gives you unique business-building opportunities, like entry to the Intel Partner Showcase, advanced training, and promotional support—all tailored to your needs. 

About TurinTech AI 

TurinTech AI is the leader in code optimisation for machine learning and data-intensive applications. Its flagship products, evoML and Artemis AI, help companies easily unlock the full potential of their code and data through Generative AI. Clients benefit from operating faster while also being more sustainable and more efficient.


Unlock the Full Potential of Your Code with GenAI.

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