Categories
Featured

‘The socket is becoming the motherboard’ — how a Samsung-backed startup wants to change computing forever by integrating everything in an elegant packaging to tackle the AI beast once and for all

[ad_1]

Many system designers are exploring chiplet-based SiPs that move beyond the limitations and costs of huge single-die implementations, but which depend heavily on silicon interposers as substrates for mounting and interconnecting the dies. 

Silicon interposers deliver a higher data rate than organic substrates, but are not without drawbacks. They are costly, proprietary and limit the number of chiplets that can be placed on one substrate due to size restrictions, while increasing TCO.

[ad_2]

Source Article Link

Categories
News

Volkswagen is Integrating ChatGPT into is cars

Volkswagen ChatGPT

Volkswagen has announced that it will be integrating ChatGPT into its vehicles and the AI language model will be available in some of the VW models with the latest generation infotainment system.

The models will include the VW ID.7, ID.4, iD.5, ID.3, the Volkswagen Tiguan, Passat and the new Golf, you can see more details below on what Volkswagen has planned for ChatGPT.

Nothing changes for the person behind the wheel. There is no need to create a new account, install a new app or activate ChatGPT: The voice assistant is activated by saying “Hello IDA” or pressing the button on the steering wheel. IDA automatically prioritises whether a vehicle function should be executed, a destination searched or the temperature adjusted. If the request cannot be answered by the Volkswagen system, it is forwarded anonymously to AI and the familiar Volkswagen voice responds.

Volkswagen ChatGPT

ChatGPT does not gain access to any vehicle data; questions and answers are deleted immediately to ensure the highest possible level of data protection. This is facilitated by Cerence Chat Pro, which leverages a multitude of sources, including ChatGPT, to enable IDA to provide accurate and relevant responses to nearly every query imaginable. The feature also prioritises security and seamless integration with IDA’s myriad capabilities, delivering ease of use for drivers.

You can find out more information about Volkswagen and ChatGPT over at the Volskwagen website at the link below, we are looking forward to finding out more details about what role AI will play in future vehicles.

Source Volkswagen
 

Filed Under: Auto News, Technology News, Top News





Latest timeswonderful Deals

Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, timeswonderful may earn an affiliate commission. Learn about our Disclosure Policy.

Categories
News

Integrating AI large language models LLMs with Knowledge Graphs

Integrating LLMs with Knowledge Graphs

In the exciting world of artificial intelligence (AI), two standout technologies are making waves: Large Language Models (LLMs) like GPT-3 and Knowledge Graphs. These tools are transforming how we handle and analyze data, leading to smarter decision-making processes. This article will take you on a journey through the practical steps of combining LLMs with Knowledge Graphs, exploring the benefits and tackling the challenges that come with this integration.

What are Knowledge Graphs?

Knowledge graphs are sophisticated databases designed to store and organize information in a way that illustrates the relationships and connections between various concepts and entities. They represent data in a network of interconnected nodes and edges, where nodes symbolize entities such as people, places, and objects, and edges denote the relationships between them.

This structure enables machines and humans alike to understand complex associations and contextual nuances within the data. Knowledge graphs are pivotal in enhancing AI capabilities, particularly in areas like semantic search, data analysis, and natural language processing, by providing a rich, contextual framework for understanding and utilizing information.

LLMs are advanced AI systems that have the ability to understand and generate human-like text. They work by predicting what word comes next in a sentence, learning from vast amounts of data. Knowledge Graphs, on the other hand, are databases that organize information about concepts and the connections between them in a way that both people and machines can understand.

When you bring LLMs and Knowledge Graphs together, they enhance each other’s capabilities. LLMs can use the structured information in Knowledge Graphs to add context to their interpretations, while Knowledge Graphs benefit from LLMs’ nuanced understanding of language. This synergy can lead to AI responses that are not only more accurate but also more relevant to the context, whether it’s for a search engine or a digital assistant.

Knowledge Graphs quick reference guide

  • Definition and Purpose:
    • Organize and represent knowledge in a structured format.
    • Facilitate understanding of relationships and connections between different concepts and entities.
  • Benefits:
    • Enhances data interoperability and integration.
    • Improves the efficiency and accuracy of data retrieval.
    • Enables more sophisticated, context-aware AI applications.
    • Supports semantic search and advanced analytics.
    • Aids in uncovering insights from complex and large datasets.
  • Applications:
    • Enhancing search engine capabilities with contextual understanding.
    • Powering recommendation systems in e-commerce and streaming services.
    • Improving natural language processing and understanding in AI systems.
    • Enabling advanced data analytics in various fields like healthcare, finance, and customer service.
  • Challenges:
    • Requires high-quality, consistent, and up-to-date data.
    • Managing and processing large volumes of data can be complex and resource-intensive.
    • Ensuring data accuracy and minimizing bias in the knowledge representation.
  • Future Potential:
    • Continues to evolve with advancements in AI and machine learning.
    • Holds immense promise for creating more intelligent, responsive, and personalized AI applications.
    • Expected to play a key role in the development of more advanced AI systems.

Consider a healthcare AI that merges the text analysis prowess of LLMs with a Knowledge Graph that maps out the relationships between diseases, symptoms, and treatments. Such an AI could provide deeper medical insights or help diagnose conditions based on the symptoms patients report. In the realm of customer service, an AI chatbot powered by an LLM can have natural conversations with customers. If this chatbot is also linked to a Knowledge Graph that contains detailed information about the company’s products or services, it can offer precise and helpful information, greatly improving the customer’s experience.

However, integrating LLMs with Knowledge Graphs is not without its hurdles. One major challenge is ensuring that the data is of high quality and consistent. Both systems need to work with data that is accurate, up-to-date, and free from bias to avoid mistakes in the AI’s output.

Data accuracy is paramount

As the amount of data grows, the integrated system must also be able to process and analyze this information both efficiently and cost-effectively. This requires sophisticated algorithms and a strong infrastructure that can manage heavy workloads. To keep data accurate and reliable, it’s crucial to have strict processes for validating and cleaning the data. Automated tools can help identify and fix errors, and regular updates are necessary to keep the Knowledge Graph current and precise.

When it comes to dealing with the scale and efficiency of the system, developers can use distributed computing. This approach allows the system to adjust its processing power based on the current needs. Using cloud-based platforms can provide the flexibility needed to scale up or down depending on demand. Additionally, optimizing the algorithms that combine LLMs with Knowledge Graphs can reduce the computational load, making the system more efficient.

The combination of LLMs and Knowledge Graphs holds immense promise for enhancing AI applications in various industries. By understanding how these technologies work together and addressing the technical challenges of data quality, scalability, and efficiency, we can create AI systems that are not only powerful but also reliable and cost-effective. As we continue to explore this integration, we can expect to see a surge of innovative AI solutions that push the boundaries of what AI can achieve.

Filed Under: Guides, Top News





Latest timeswonderful Deals

Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, timeswonderful may earn an affiliate commission. Learn about our Disclosure Policy.

Categories
News

How Shopify is integrating AI into its e-commerce services

Shopify, a prominent e-commerce platform, is bringing to life a vision of a world where tools used for online businesses not only simplify workloads but also enhance creativity and productivity. They achieve this through strategic integration of artificial intelligence (AI) into their services. This transformation is revolutionizing the online retail experience for all involved, from employees and customers to partners who rely on Shopify’s robust system.

Shopify is embracing Microsoft’s Copilot, an AI-powered assistant being integrated throughout Microsoft products and services and available in GitHub. This tool is revolutionizing the way developers work by streamlining engineering workflows and making project management more collaborative. Copilot is designed to help you work smarter, not harder, by taking on the heavy lifting of coding, allowing developers to focus on more complex and creative tasks.

Shopify AI features

At the core of Shopify’s technological advancements lies its highly scalable checkout system. This system is built to handle the intense demands of flash sales and sudden spikes in website traffic, ensuring that your business stays up and running when it matters most. The ability to maintain operations during peak shopping times is crucial for staying competitive in the fast-paced world of e-commerce.

Other articles you may find of interest on the subject of Microsoft Copilot

Shopify AI integration

One of the most significant impacts of AI on Shopify has been the deployment of large language models (LLMs). These advanced AI systems are incredibly adept at generating content, from product descriptions to marketing materials and customer communications. With LLMs, you can shift your attention to making strategic business decisions while AI takes care of creating compelling content that resonates with your audience.

But Shopify’s use of AI doesn’t stop at content creation. Internally, AI is also being used to enhance customer service and evaluate the quality of partner apps. These AI tools are carefully crafted to improve the quality and efficiency of customer interactions and to ensure that partner apps meet Shopify’s high standards. This commitment to excellence creates a seamless and supportive environment for everyone within the Shopify ecosystem.

AI is also playing a crucial role in automating routine tasks on the platform. By handling these tasks, AI frees you up to invest your time and energy in areas that require a human touch, such as creative thinking and high-impact activities. Shopify views AI as a tool to augment your abilities, not replace them, reinforcing the idea that technology should empower people, not diminish their roles.

Shopify integrates Copilot into its systems

The decision to integrate Copilot into Shopify’s system was made with the intention of fostering innovation and ensuring a smooth fit with the existing infrastructure. The impact on developer productivity and satisfaction has been remarkable. Copilot has quickly become a favorite among engineers, with a significant portion of code now being authored by the tool. The high acceptance rate of Copilot is a testament to its effectiveness and the positive change it has brought to the development process.

Microsoft Copilot

However, the integration of Copilot was not without its challenges. Engineers had to adjust to new ways of working and overcome the initial learning curve associated with the tool. Despite these hurdles, the reception of Copilot within Shopify has been overwhelmingly positive. Shopify has also taken proactive steps to address the legal implications of using AI-generated code. Working closely with legal teams has been essential in navigating the complexities of AI usage, ensuring that all operations comply with legal and ethical standards.

Shopify’s strategic approach to AI, exemplified by the integration of Copilot, reflects a forward-thinking mindset that prioritizes efficiency, innovation, and the human element. The enthusiastic adoption and positive feedback regarding Copilot at Shopify indicate a strategy that not only addresses the current needs of the e-commerce industry but also sets the stage for future technological advancements.

AI e-commerce solutions

As the e-commerce landscape continues to evolve, Shopify’s commitment to innovation positions it as a leader in the industry. By harnessing the power of AI, Shopify is not just keeping up with the changes; it’s driving them. The company’s focus on enhancing workflow efficiency, boosting developer productivity, and maintaining a scalable system ensures that businesses using Shopify are equipped to thrive in the digital marketplace.

For those involved in e-commerce, whether you’re a developer, merchant, or partner, Shopify’s AI integration offers a glimpse into a future where technology and human ingenuity work hand in hand. The platform’s ability to adapt and innovate serves as a reminder that in the world of online retail, the only constant is change, and staying ahead of the curve requires embracing the tools that will shape the future of the industry.

Filed Under: Technology News, Top News





Latest timeswonderful Deals

Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, timeswonderful may earn an affiliate commission. Learn about our Disclosure Policy.