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Artificial Intelligence For The Best Customer Services

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Artificial Intelligence For Best Customer Services,Startup Stories,2018 Latest Business News & Updates,Startup Stories India,Latest Technology News 2018,AI For Best Customer Services,Artificial Intelligence Features,AI Customer Service Sector

Implementing Artificial Intelligence improves the features and working of the customer service sector. It helps the companies to handle the task easily but has some disadvantages too. It might not be possible for a human to stay on for 24/7 to serve, but it is not a problem for artificial intelligence. They can give live services irrespective of time. The problem with the robotic technology is that they can’t understand all languages or some special characters, they just work with features pre-installed in them. Let us have a brief overview of the Artificial Intelligence in customer service.

Artificial Intelligence for Sudden Change in Service Sector:

Combining Artificial Intelligence and Machine Learning gives innovative and happy results. It works efficiently with fast servers. There are no time limitations for the AI (Artificial Intelligence) systems, sometimes technical issues may be raised which can be solved in no time.

Increasing Productivity and Accuracy:

Artificial Intelligence enables customer service agents to serve a customer in better and more efficient manner. Previously customer service agents should be familiar with each and every aspects of the company, but now it is not that necessary after artificial intelligence coming to use. It also serves the customer on the real-time basis, without any delay. Artificial Intelligence also helps to gather the information quicker and accurate.

Usage of Collected Customer Data:

The huge amount of customer data collected by the companies will be as the knowledge base for the artificial intelligent system. The more the data fed into the system, the more efficient it works and handles customers efficiently.

Multiple Language Support:

All the Multi-National Companies has the customer base from different regions, who speak different languages. And it is highly impossible to set a customer care center to handle in all the languages preferred by the customers. This can be done by using machines, making a machine learn multiple languages is easy. Hence the machines can handle it without much risk.

Auto Respond to Bulk Emails:

The ticket supervision system with Artificial Intelligence helps your support center by answering instantly to some general queries. All company’s content is retrieved by the system and it helps to answer a greater number of emails automatically.

ChatBots:

Chatbots are the automatic response system which gives a response to the customer queries automatically by searching the knowledge base, company’s database and approved external sources. Chat Bots give the real time and personalized responses to the customers. By this, if the physical agent is not active, the query of the customer can be solved.

Also, Read HOW ARTIFICIAL INTELLIGENCE AND CHATBOTS WILL CHANGE STARTUPS

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Artificial Intelligence

Microsoft Partners with Indian Government to Skill 500,000 in AI

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Microsoft Partners with Indian Government to Skill 500,000 in AI

Microsoft has announced a significant partnership with the Indian government to empower the country’s workforce with AI skills. This collaboration aims to skill 500,000 students and educators in AI technologies by 2026, fostering a strong foundation for AI innovation in India.

Key Initiatives

AI Skilling Program

The partnership will focus on skilling 500,000 individuals, including:

  • Students
  • Educators
  • Developers
  • Government officials
  • Women entrepreneurs

This comprehensive approach aims to create a diverse pool of talent equipped with essential AI skills.

AI Centers of Excellence

The establishment of AI Catalysts, also known as Centers of Excellence, will promote rural AI innovation and support 100,000 AI developers. These centers will foster community-driven AI solutions through:

  • Hackathons
  • Community-building initiatives
  • An AI marketplace

Focus on Critical Sectors

The collaboration will prioritize developing AI solutions for key sectors such as:

  • Healthcare
  • Education
  • Accessibility
  • Agriculture

This targeted approach addresses specific challenges faced by India while leveraging AI to enhance productivity and efficiency.

Investing in AI Infrastructure

Microsoft plans to invest $3 billion in India over the next two years. This investment will include the establishment of new data centers with a focus on sustainability, enhancing the country’s digital infrastructure and capacity for AI development.

Nadella’s Vision

Microsoft CEO Satya Nadella emphasized the importance of AI as a “guardian angel” for the future, highlighting India’s unique position as a leader in AI adoption. He encouraged the country to focus on frontier AI research and development, particularly in creating local language AI tools that cater to India’s diverse linguistic landscape.

Government Collaboration

The partnership with the Ministry of Electronics and Information Technology (MeitY) reflects the Indian government’s commitment to fostering AI innovation and developing a skilled workforce. This collaboration aligns with the government’s broader objective of enhancing digital capabilities across various sectors.

Overall Impact

This collaboration marks a significant step towards empowering India’s workforce with essential AI skills and driving innovation in the country. By fostering a robust AI ecosystem, India can leverage the power of artificial intelligence to address its unique challenges and unlock new opportunities for economic growth and social development.

Conclusion

Microsoft’s partnership with the Indian government represents a transformative initiative aimed at building a skilled workforce capable of driving AI innovation. Through targeted training programs, investment in infrastructure, and strategic focus on critical sectors, this collaboration is poised to make a lasting impact on India’s economic landscape and technological advancement.

 

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Artificial Intelligence

Google Unveils Veo 2: A New Era of AI Video Generation!

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Google-introduces-VEO

Google has made significant strides in the field of AI with the introduction of its latest video generation model, Veo 2. Designed to rival OpenAI’s Sora, Veo 2 promises to deliver hyper-realistic, high-quality videos in 4K resolution, marking a notable advancement in AI-generated content.

Key Features of Veo 2

  • Realistic Motion: Veo 2 excels in generating videos with natural and fluid movements, simulating real-world physics and human dynamics. This improvement allows for more lifelike representations in generated videos.
  • High-Quality Output: The model produces stunning visuals with intricate details and vibrant colors, enhancing the overall viewing experience. Users can expect videos that not only look good but also convey a sense of realism.
  • Benchmark Performance: Google claims that Veo 2 outperforms other leading video generation models based on human preference evaluations. In head-to-head comparisons, it was preferred by 59% of participants over OpenAI’s Sora, which garnered only 27%.
  • Extended Video Lengths: Unlike many competitors, Veo 2 can generate videos longer than two minutes, significantly enhancing its utility for creators looking to produce more comprehensive content.

Advanced Capabilities

Veo 2 is integrated into Google Labs’ video generation tool, VideoFX, and includes several advanced features:

  • Cinematic Effects: Users can specify cinematic jargon such as lens types and shot angles (e.g., low-angle tracking shots or close-ups), allowing for tailored video outputs that meet specific creative requirements.
  • Complex Scene Generation: The model can process complex requests, including genre specifications and cinematic effects, making it versatile for various applications from entertainment to education.

Imagen 3 and Whisk: A Powerful Image Creation Duo

Alongside Veo 2, Google has introduced two additional models:

  • Imagen 3: This versatile image generation model is capable of producing a wide range of styles, from photorealistic to abstract. It has been improved to deliver brighter and better-composed images.
  • Whisk: This new experimental tool allows users to create new images by combining multiple input images, enabling unique output styles and creative possibilities.

Addressing Challenges in AI Video Generation

While these advancements are impressive, challenges remain in creating complex scenes with intricate motion and maintaining consistency throughout a video. Google acknowledges these hurdles but is committed to ongoing research and development to enhance the capabilities of its AI models further.

Safety Measures

To combat misinformation and ensure proper attribution, all videos generated by Veo 2 will include a visible and invisible watermark called SynthID. This feature is part of Google’s commitment to responsible AI development, helping to identify AI-generated content and mitigate potential misuse.

Future Prospects

As these tools become more accessible, they have the potential to revolutionize various industries, including entertainment, advertising, and education. The integration of Veo 2 into platforms like YouTube Shorts is planned for 2025, further expanding its reach and impact.

Conclusion

Google’s introduction of Veo 2 marks a significant leap forward in AI video generation technology. With its ability to produce high-quality, realistic videos and advanced cinematic capabilities, Veo 2 is set to reshape content creation across multiple sectors. As Google continues to innovate in this space, the future of AI-generated content looks promising—provided that ethical considerations are prioritized alongside technological advancements.

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Artificial Intelligence

Microsoft’s New Phi-3.5 Models: A Leap Forward in AI!

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Microsoft's New Phi-3.5 Models: A Leap Forward in AI!

Microsoft has made significant strides in the field of AI with the release of its new Phi-3.5 models. This series includes Phi-3.5-MoE-instruct, Phi-3.5-mini-instruct, and Phi-3.5-vision-instruct, which demonstrate impressive performance, surpassing industry benchmarks and rivaling models from leading AI companies like OpenAI, Google, and Meta.

Key Highlights of the Phi-3.5 Models

  • Phi-3.5-MoE-instruct: This powerful model features 41.9 billion parameters, excelling in advanced reasoning tasks and outperforming larger models such as Llama 3.1 and Gemini 1.5 Flash. It supports multilingual capabilities and can process longer context lengths, making it versatile for various applications.
  • Phi-3.5-mini-instruct: A lightweight yet potent model with 3.8 billion parameters, it demonstrates strong performance in long-context tasks, outperforming larger models like Llama-3.1-8B-instruct and Mistral-Nemo-12B-instruct-2407. This model is optimized for quick reasoning tasks, making it ideal for applications such as code generation and logical problem-solving.
  • Phi-3.5-vision-instruct: With 4.15 billion parameters, this model excels in visual tasks, surpassing OpenAI’s GPT-4o on several benchmarks. It can understand and reason with images and videos, making it suitable for applications that require visual comprehension, such as summarizing video content or analyzing charts.

Open-Sourcing the Future of AI

Microsoft’s commitment to open-sourcing these models aligns with its vision of democratizing AI technology. By making these models available on Hugging Face under an MIT license, Microsoft empowers researchers and developers to build innovative AI applications without the constraints typically associated with proprietary software.

The Phi-3.5 models have the potential to revolutionize various industries, including healthcare, finance, and education. Their advanced capabilities can help automate tasks, improve decision-making processes, and enhance user experiences across different platforms.

Advanced Features

One of the standout features of the Phi-3.5 series is its extensive context window of 128,000 tokens, which allows the models to process large amounts of data effectively. This capability is crucial for real-world applications that involve lengthy documents or complex conversations, enabling the models to maintain coherence over extended interactions.

The training process for these models was rigorous:

  • The Phi-3.5-mini-instruct was trained on 3.4 trillion tokens over a span of ten days.
  • The Phi-3.5-MoE-instruct required more extensive training, processing 4.9 trillion tokens over 23 days.
  • The Phi-3.5-vision-instruct was trained on 500 billion tokens using a smaller training period of six days.

These extensive training datasets comprised high-quality, reasoning-dense public data that enhanced the models’ performance across numerous benchmarks.

Conclusion

As AI continues to evolve, Microsoft’s Phi-3.5 models are poised to play a crucial role in shaping the future of technology by offering smaller yet highly efficient solutions that outperform larger counterparts in specific tasks. By focusing on efficiency and accessibility through open-source initiatives, Microsoft is addressing the growing demand for powerful AI tools that can be deployed in resource-constrained environments as well as large-scale cloud settings.

The introduction of these models not only signifies a leap forward in AI capabilities but also challenges traditional notions about model size versus performance in the industry, potentially paving the way for more sustainable AI development practices in the future.

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