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A generation of artificial intelligence will reshape the future technological landscape
A generation of artificial intelligence will reshape the future technological landscape
Over the past 10 years, new innovations have emerged in the technology field, from traditional systems to cloud computing services to ransomware protection. Technology teams around the world are turning their focus to streamlining multi-cloud operations with the goal of innovating without increasing costs. Rapid adoption of generative artificial intelligence (GenAI) tools is critical to staying competitive.
However, who is responsible for the behavior of artificial intelligence? How to ensure responsible AI development and ethical innovation? How do we maximize the full capabilities of technology without compromising security, compliance, data sovereignty, or our ethical obligations to respect the privacy of others?
What is Big Business Doing?
GenAI is a clear catalyst for innovation, and responsibility is front and center with the biggest technology pioneers of our generation.
At this year’s VMware Explore conference, VMware President Sumit Dhawan and Aon CTO Rajeev Khanna discussed one of three key topics: responsible GenAI. The global professional services company has approximately 50,000 employees in 120 countries and is a loyal user of VMware solutions. According to Khanna, GenAI "opens up a whole new set of opportunities." Aon is in the risk advisory business, which means it's prudent to balance excitement about the future with a stable, cautious approach, it said.
Indeed. It's easy to get enthusiastic about the next shiny thing in tech, but there are many hurdles that need to be overcome to achieve innovation and gain enterprise-wide buy-in. Khanna emphasizes building and maintaining a culture of responsible AI use and governance, and never losing sight of the fundamental role of human oversight for ethical and responsible AI use.
Applying GenAI to all enterprises At the VMware Explore 2023 conference, significant progress was announced. The partnership with Nvidia resulted in the VMware Private AI Foundation, integrating Nvidia enterprise AI into a versatile platform. This allows IT to effectively manage large language models with privacy, security, and performance across a variety of AI/ML workloads.
The VMware Tanzu portfolio simplifies container-based application management and enhances security, while Edge Cloud Orchestrator enables rapid provisioning of edge locations. Additional enhancements include a cloud control plane, stronger ransomware protection and performance improvements to VMware Cloud Foundation, resulting in a powerful platform for traditional, modern and AI/ML workloads across the cloud and edge.
We are Being in a transformational phase that enables organizations to optimize their business, reduce waste and drive innovation. At VMware Explore, the business once again emerged as a key player, equipping technology departments to increase productivity, accelerate innovation and drive sustainable success.
What can we do when it comes to GenAI?
The VMware Explore panel discussion titled “Responsible Artificial Intelligence: What Role Should Humans Play?” highlighted that we also have a lack of clarity on the role humans will play in the dynamic convergence of GenAI and multi-cloud technologies. s answer. The panel was moderated by Richard Munro, head of the Office of the Chief Technology Officer, who has a track record of exploring the ethical principles that guide the development of AI systems and human involvement. First, data journalist, NYU A. Meredith Broussard, associate professor at the Arthur L. Carter Journalism Institute, defines AI as "complex and beautiful mathematics." He said that when talking about artificial intelligence, many people will think of "Terminator", "Star Trek" or "Star Wars", but we need to distinguish between reality and imagination. Artificial intelligence is a kind of "pattern copying" where data is fed into a computer, the computer builds a model, and the model displays mathematical patterns to make decisions, generate new text, images, or audio, and predict outcomes.
What resonates, however, is the discussion around how artificial intelligence will change culture. Broussard also agreed on the importance of combating bias and misunderstanding in AI systems, but also hypothesized that there will be social problems manifested by AI bias
Expert panel further discussed private artificial intelligence The problem. Private AI refers to the use of small models that are easy to train. Fewer resources means a lower carbon footprint and greater accuracy. Private AI enables organizations to iterate faster without having a huge impact on the environment. It involves not only artificial intelligence, but also aspects such as cloud computing, customers, content and environment
Artificial intelligence is a long game, in short. We should avoid the temptation to rush to win in pursuit of early success. More importantly, considering the ability to choose as part of artificial intelligence
Paving the way for a future of ethical intelligenceThe panel stressed that people should feel safe asking questions , to guide artificial intelligence to produce expected results. Our responsibility is to define what AI should and should not do, and to raise awareness about AI so people understand how it can amplify existing bias and disinformation
- Reliable:The reliability of artificial intelligence depends on high-quality data and the reduction of bias in the model. Remember Apple’s Health app back in 2014? It didn’t include menstrual tracking. Reducing bias and building adequate representation in models can improve reliability and accountability.
- Ethics:The purpose of artificial intelligence deployment must be consistent with the improvement of society and comply with regulations. Embedding ethical principles in AI models ensures responsible use.
- Security:It is crucial to protect the learning model of artificial intelligence because it can fall into unexpected hands. Protecting sensitive data, employee information, and customer data is necessary, and knowing whether an AI model is open source or proprietary is critical to security.
- Privacy:The nature of the data determines its privacy requirements. Determining whether the data is highly sensitive, mission critical, or regulated is critical to determining what should or should not be included in an AI model.
- Transparency: Communicate openly and transparently with employees, customers and supply chain partners about the role of AI to foster trust and ensure everyone understands the purpose and potential of AI Influence.
- Unpretended:To address the challenge of opacity in AI, it is critical to understand the inner workings of the algorithm, how it drives results, and the cascading effects of changing variables within the model to increase transparency. of.
- Standards:Implementing guardrails is a critical aspect of ensuring responsible and ethical AI development. Guardrails help set boundaries and guidelines to prevent AI systems from causing harm or making unethical decisions.
However, the most important thing is to put people first. GenAI’s true potential lies in its accessibility to people of all ages and professions, making it a tool that everyone can use to ask questions. Technology serves humanity
What does responsible artificial intelligence mean?
Who does the responsibility for artificial intelligence belong to? In short, everyone. Chris Wolf points out that there is still a lot we don’t know about it, and there are no industry standards
Organizations, experts and policymakers share collective responsibility for shaping the trajectory of artificial intelligence. As we look to GenAI to make decisions and provide insights, solutions like the VMWare platform allow us to pivot and adapt with confidence. We live in rapidly changing scenarios and an ever-changing economy, and the models used must be elastic and dynamic. GenAI in the intelligent cloud allows flexibility. Participate in discussions that promote ethical AI development and deployment. Build the infrastructure for AI first, then scale. Most importantly, as Wolf advises, keep asking questions and staying curious.
Imagine the possibilities for GenAI in business... if done thoughtfully and responsibly.
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