Today, there is a paradigm shift from traditional AI systems that use statistical and mathematical probabilistic algorithms to those that use machine learning (ML) and deep learning (DL) models. As per Gartner, there are 34 different branches of AI system design in existence today. AIOps in cloud operations, DataOps in data engineering, predictive analytics in data science, and MLOps in industrial applications are some of the examples of new age AI applications.
Ray Kurzweil coined the term 'singularity' in AI, which means bringing AI closer to human intelligence (or natural intelligence). To achieve the highest level of accuracy in ML training, modelling and functioning, it is of utmost important to ensure fairness and correct any bias in AIML implementation. Bias cannot occur on its own but is the result of human inputs during the various stages of developing the AIML-based solution.
When collecting data for training the model in ML, one must ensure the data is distributed fairly and that there is no bias. In the same way, when we label and group the data, train the model to simulate human-like thinking, deploy the model and interpret the results, we must do away with any pre-judgement or biased interests.
For example, bias with respect to race, income, sexual orientation, gender, religion, must be avoided when preparing the training data, training the system and interpreting the results from the ML execution.
There are many popular tools like IBM’s AI Fairness 360, Microsoft’s Fairlearn and Google’s What-if that are very useful to identify any bias in the training model and data collection.
Addressing bias in AI systems
Diese Geschichte stammt aus der April 2024-Ausgabe von Open Source For You.
Starten Sie Ihre 7-tägige kostenlose Testversion von Magzter GOLD, um auf Tausende kuratierte Premium-Storys sowie über 8.000 Zeitschriften und Zeitungen zuzugreifen.
Bereits Abonnent ? Anmelden
Diese Geschichte stammt aus der April 2024-Ausgabe von Open Source For You.
Starten Sie Ihre 7-tägige kostenlose Testversion von Magzter GOLD, um auf Tausende kuratierte Premium-Storys sowie über 8.000 Zeitschriften und Zeitungen zuzugreifen.
Bereits Abonnent? Anmelden
Helgrind: Detecting Synchronisation Issues in Multithreaded Programs
Let's explore how Helgrind can be used to detect and debug multithreading issues with the help of a multithreaded C program.
The Perfect Process of Booting a PC
Booting a PC seems as simple as eating a cake. But are you aware of all that goes on behind-the-scenes to bake a delicious cake or seamlessly boot a PC?
Exploring eBPF and its Integration with Kubernetes
eBPF, a game-changing technology that extends the capabilities of the Linux kernel, offers significant advantages for Kubernetes networking. It also greatly improves Kubernetes observability by capturing detailed telemetry data directly from the kernel. Read on to find out how its integration with Kubernetes has immense benefits.
Deploying Generative AI LLMs on Docker
Built on massive datasets, large language models or LLMS are closely associated with generative Al. Integrating these models with Docker has quite a few advantages.
Containerisation: The Cornerstone of Multi-Cloud and Hybrid Cloud Success
Open source containerisation software provides the flexibility, cost-effectiveness, and community support needed to build and manage complex multi-cloud and hybrid cloud environments. By leveraging this software, businesses can unlock the full potential of multicloud and hybrid cloud architectures while minimising vendor lock-in risks.
From Virtual Machines to Docker Containers: The Evolution of Software Development
Containerisation and Kubernetes have eased software development, making it faster and better. Let's see where these are headed, looking at trends that are making life easier for developers.
India's Leap in Supercomputing: Innovating for Tomorrow
As India strides towards self-sufficiency in supercomputing, embracing this evolution isn't just an option-it is pivotal for global competitiveness and technological leadership.
SageMath: A Quick Introduction to Cybersecurity
In the previous articles in this SageMath series, we delved into graph theory and explored its applications using SageMath. In this seventh article in the series, it is time to shift our focus to another crucial subfield of computer science: cybersecurity and cryptography.
Efficient Prompt Engineering: Getting the Right Answers
OpenAl's GPT-3 and GPT-4 are powerful tools that can generate human-like text, answer questions, and provide insights. However, the quality of these outputs depends heavily on how you frame the input, or prompt. Efficient prompt engineering ensures you get the right answers by designing inputs that guide the AI towards relevant, clear, and useful responses. Let's find out how to craft effective prompts with examples.
Analysing Linus Torvald's Critique of Docker
This article looks at Docker's security flaws, particularly its shared-kernel model, and contrasts it with traditional VMs for better isolation. It discusses Linus Torvalds' concerns, explores mitigation techniques, and proposes a roadmap for building a more secure containerisation platform using hardware-assisted virtualisation, true isolation, and a robust orchestration layer.