#generative ai Accenture

[dhallblogs]

Accenture Claims Generative AI to Merge Physical and Digital Worlds.

New Delhi: New research from Accenture finds that generative AI and other rapidly evolving technologies are ushering in a bold new future for business as physical and digital worlds become inextricably linked.

ALSO READ MORE-https://apacnewsnetwork.com/2023/03/accenture-claims-generative-ai-to-merge-physical-and-digital-worlds/

[jcmarchi]

How to Hire – and When to Fire – a Chief AI Officer

New Post has been published on https://thedigitalinsider.com/how-to-hire-and-when-to-fire-a-chief-ai-officer/

How to Hire – and When to Fire – a Chief AI Officer

Generative AI is quickly becoming part of corporate agendas worldwide. Nevertheless, most organizations are still struggling to get their GenAI operations up and running.

A recent Accenture survey revealed that only 27% of executives are in a position to scale such capabilities. Indeed, more than 70% are still at square one, trying to determine how to best leverage them. As a result of this current lag in AI readiness, a new corporate role has emerged: the Chief AI Officer (CAIO).

However, the ins and outs of GenAI as a business solution will eventually catch on, much like the Internet did; companies and their employees will adapt to new technologies, best practices will be established, and regulations will be set in place.

While CAIOs are indeed essential in facilitating and resolving critical AI deployment over the next few years or so, the role will eventually grow redundant. Given the inevitable maturation of GenAI, this latest C-suite position is all but temporary.

Popularity Contest

Many mid to large-sized companies have found themselves unprepared to scale GenAI technologies. 11% have responded by appointing a CAIO while another 21% (and growing) are actively seeking one out.

Top tier media including Bloomberg, Business Insider, and Forbes have covered the rise of this new position – the New York Times even went as far as declaring it the “hottest job” in corporate America. Still, the actual responsibilities of a CAIO remain quite ambiguous. Job descriptions often include vague language like “You’ll be in charge of integrating AI strategies, deploying AI, and mitigating AI risks.”

Top 3 Considerations

In reality, the responsibilities of a Chief AI Officer can be divided into three main considerations – the first of which pertains to the kinds of AI solutions currently available.

GenAI tools are improving every week; it’s crucial for the AI executive to have their finger on the pulse of the current offerings and prices in the AI marketplace. Additionally, knowing which AI solutions offer a steady product development cycle is critical information when contracting an AI vendor. A CAIO must also supervise the deployment of any such solution across the entire organization.

Second, CAIOs need to determine the AI solutions that are most relevant for each department. Every department has its own unique tasks and objectives, and therefore will require different AI tools. Thus, a CAIO needs to foster open communication with department heads to best assess the most cumbersome, time consuming, and error-prone challenges facing each department, as well as the active AI tools which can best streamline those tasks.

Moreover, it’s the CAIO’s responsibility to ensure employees are proficient in using these AI tools. According to a recent report, only 35% of workers say their employers provide the necessary tools for AI adoption – even fewer receive usage guidance (29%) or requisite training (22%). To this end, CAIOs must bolster the adoption rate of AI amongst employees as well as the company-wide impact these solutions yield – such as cost savings, time-to-market, revenue, and net promotor scores.

The third consideration concerns awareness of AI regulations. A vendor’s solution can be the gold standard, offer competitive pricing, and align perfectly with a company’s objectives – only to be rendered undeployable in the face of newly established regulations. AI regulation is in its infancy, and GenAI technologies will surely be impacted by emerging rules. For this reason, it is critical that CAIOs stay abreast of AI regulations and take current trends into account throughout the process of choosing the right AI solutions.

When to Let Go

While CAIOs are key for companies looking to overcome hurdles and expedite AI integration into office workflows, their services won’t be necessary forever. Once core integrations have been established – CIOs and CISOs should be able to take the reins, curtailing the continued need for a CAIO.

But at what point does a company know when this point has arrived? It’s important for companies, while remaining flexible as the technology continues to evolve, to establish benchmarks and milestones from the get-go in order to measure the progress of their newly appointed CAIO—and determine if the point has come to begin phasing them out.

Measuring Progress

Setting up clear benchmarks and milestones from the beginning ensures that the CAIO’s contributions are measurable and aligned with the company’s strategic goals. For instance, these could include achieving a specific level of AI integration across departments, demonstrable improvements in operational efficiency, compliance with new AI regulations, or significant advancements in employee AI proficiency. Each milestone should be specific and quantifiable, such as reducing operational costs by a certain percentage or achieving a set rate of AI adoption across various business units.

With these milestones in place, not only can a company gauge the progress of AI integration, but also strategically plan for the future without depending solely on the CAIO. This foresight is critical as it provides both the CAIO and the company with a clear view of the role’s trajectory and potential sunset.

Planning for the Transition

With established benchmarks and milestones, it’s also crucial to have a transition process ready when those targets are met. This process involves a structured handover where the CAIO collaborates closely with the CIO and CISO to ensure a seamless transfer of duties. Essential elements of a successful transition include:

Knowledge Transfer: The CAIO should ensure that all AI-related strategies, projects, and operational knowledge are thoroughly documented and shared with the CIO and CISO.

Advisory Role: Transitioning from a direct management role to an advisory role can help maintain continuity and stability. The CAIO can support the CIO and CISO by providing insights and guidance on AI-related matters as they take over the reins.

Monitoring and Adjustments: Post-transition, it’s important to monitor the outcomes and make adjustments as needed. This ensures that the integration of AI continues to meet the strategic goals without the CAIO’s direct involvement.

By planning for the eventual transition of the CAIO’s responsibilities to other C-suite executives, companies can ensure that their investment in AI governance and integration delivers sustained value over the long term. This strategic foresight not only optimizes the contributions of the CAIO but also enhances the overall resilience and adaptability of the organization in the face of evolving AI technologies.

The Clock is Ticking

The competitive implications of emerging AI technologies can’t be ignored. For companies struggling to get a grip on GenAI, hiring an executive dedicated to extracting value from the red-hot tech is a practical, strategically sound move – as long as their role is clearly defined and aligned with a company’s mission and objectives.

However, as was the case for Chief Metaverse Officers or Chief Digital Officer positions, the role of the CAIO is on track to become redundant within the corporate hierarchy. Companies must therefore be ready to undo the role of a CAIO once initial adoption and company-wide integrations are complete by establishing measurable benchmarks and milestones and equipping themselves with a clear, transparent transition plan.

For those looking to hire – or be hired as – Chief AI Officers, the time is now.

[jobsinfinite]

Exciting News : Generative AI Studio Launches for Enterprises By Accenture In India

Accenture A global leader in technology and consulting. Has raised the bar yet again with the launch of its state of the art generative AI studio in Bengaluru, India. This pioneering move represent a strategic Amalgamation of Accenture Robust Tata an AI Powers. In a new era of innovation and transformation. Accenture Hub for Innovation and Reinvention. Set within Accenture’s Innovation Hub,…

[vlruso]

Accenture creates a Knowledge Assist solution using generative AI services on AWS

📢 Exciting News! Accenture has partnered with AWS to create Knowledge Assist, a revolutionary generative AI solution that streamlines information retrieval for enterprises. By leveraging AWS generative AI services, Knowledge Assist understands and answers user queries accurately, improving employee productivity and customer satisfaction. Read more about this game-changing solution: [link](https://ift.tt/easVnxZ) #Accenture #AWS #AI #KnowledgeManagement #Productivity #CustomerSatisfaction #GenerativeAI #Innovation #Technology List of Useful Links: AI Scrum Bot - ask about AI scrum and agile Our Telegram @itinai Twitter -  @itinaicom

[mariacallous]

The US Patent and Trademark Office banned the use of generative artificial intelligence for any purpose last year, citing security concerns with the technology as well as the propensity of some tools to exhibit “bias, unpredictability, and malicious behavior,” according to an April 2023 internal guidance memo obtained by WIRED through a public records request. Jamie Holcombe, the chief information officer of the USPTO, wrote that the office is “committed to pursuing innovation within our agency” but are still “working to bring these capabilities to the office in a responsible way.”

Paul Fucito, press secretary for the USPTO, clarified to WIRED that employees can use “state-of-the-art generative AI models” at work—but only inside the agency’s internal testing environment. “Innovators from across the USPTO are now using the AI Lab to better understand generative AI's capabilities and limitations and to prototype AI-powered solutions to critical business needs,” Fucito wrote in an email.

Outside of the testing environment, USPTO staff are barred from relying on AI programs like OpenAI’s ChatGPT or Anthropic’s Claude for work tasks. The guidance memo from last year also prohibits the use of any outputs from the tools, including images and videos generated by AI. But Patent Office employees can use some approved AI programs, such as those within the agency’s own public database for looking up registered patents and patent applications. Earlier this year, the USPTO approved a $75 million contract with Accenture Federal Services to update its patent database with enhanced AI-powered search features.

The US Patent and Trademark Office, an agency within the Department of Commerce, is in charge of protecting inventors, awarding patents, and registering trademarks. It also “advises the president of the United States, the secretary of commerce, and US government agencies on intellectual property (IP) policy, protection, and enforcement,” according to the USPTO’s website.

At a Google-sponsored event in 2023, Holcombe, the author of the guidance memo, said government bureaucracy makes it difficult for the public sector to use new technologies. “Everything we do in the government is pretty stupid, when you compare it to the commercial world, right?” he said. Holcombe specifically cited cumbersome budgeting, procurement, and compliance processes, arguing that they hamper the government's ability to rapidly adopt innovations like artificial intelligence.

The USPTO is not the only government agency to ban staff from using generative AI, at least for some purposes. Earlier this year, the National Archives and Records Administration prohibited the use of ChatGPT on government-issued laptops, according to 404 Media. But soon afterward, the National Archives hosted an internal presentation that encouraged employees to “think of [Google’s] Gemini as a co-worker.” During the meeting, some archivists reportedly expressed concerns about the accuracy of generative AI. Next month, the National Archives is planning to release a new public chatbot for accessing archival records developed with technology from Google.

Other US government agencies are using—or avoiding—generative AI in different ways. The National Aeronautics and Space Administration, for example, specifically banned the use of AI chatbots for sensitive data. NASA did decide, however, to experiment with the technology for writing code and summarizing research. The agency also announced last week that it’s working with Microsoft on an AI chatbot that can aggregate satellite data to make it easily searchable. That tool is available only to NASA scientists and researchers, but the goal is to “democratize access to spaceborne data.”

[ericvanderburg]

Google Cloud CEO and Accenture CEO talk investments in generative AI and cybersecurity

http://i.securitythinkingcap.com/TCXkCl

[bloggerkeke]

How is AI transforming every aspect of human life?

AI is transforming every aspect of human life by revolutionizing the way we work, communicate, learn, and live. Here are some key areas where AI is making a significant impact:

What is Artificial Intelligence?

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that can perform tasks requiring human-like cognitive abilities. It involves machine learning, natural language processing, computer vision, and other advanced techniques.

How does it impact every industry?

AI has the potential to revolutionize every industry by automating processes, analyzing vast amounts of data, and making intelligent predictions. It improves efficiency, enhances decision-making, and drives innovation across sectors such as healthcare, finance, manufacturing, and transportation.

How does it impact every individual?

AI impacts individuals by providing personalized experiences, virtual assistants, and smart devices. It enhances daily life through voice recognition, recommendation systems, and virtual customer support. AI-powered technologies make our lives easier, more convenient, and efficient.

AI is transforming every aspect of human life by revolutionizing the way we work, communicate, learn, and live. Here are some key areas where AI is making a significant impact:

1. Healthcare: 

AI is enhancing medical diagnosis, drug discovery, and personalized treatment plans. It helps analyze vast amounts of patient data, identify patterns, and provide accurate predictions for disease prevention and early intervention.

According to Accenture, AI in healthcare could potentially save up to $150 billion annually for the U.S. healthcare economy by 2026.

The global AI in healthcare market is projected to reach $45.2 billion by 2026, growing at a compound annual growth rate (CAGR) of 44.9% from 2019 to 2026.

2. Education: 

AI is revolutionizing education by enabling personalized learning experiences, adaptive tutoring, and intelligent assessment systems. It helps tailor educational content to individual student needs, track progress, and provide timely feedback for better learning outcomes.

The global AI in education market is expected to reach $3.68 billion by 2025, with a CAGR of 38.17% from 2018 to 2025.

A study by the American Institutes for Research found that AI-powered tutoring systems have a positive impact on student learning outcomes, resulting in an average percentile gain of 28 points.

3. Transportation: 

AI is driving advancements in autonomous vehicles, optimizing traffic management systems, and improving transportation efficiency and safety. It enables self-driving cars, real-time navigation, and predictive maintenance, revolutionizing the way we commute and travel.

The global autonomous vehicle market is projected to reach $556.67 billion by 2026, with a CAGR of 39.47% from 2019 to 2026.

According to the National Highway Traffic Safety Administration, AI-powered advanced driver-assistance systems (ADAS) have the potential to reduce traffic fatalities by up to 94%.

4. Communication: 

AI-powered language translation, natural language processing, and speech recognition technologies are transforming communication. Chatbots, virtual assistants, and language translation tools facilitate seamless cross-cultural communication and enhance accessibility.

The global AI in communication market is expected to reach $3.5 billion by 2026, growing at a CAGR of 34.7% from 2019 to 2026.

AI-powered language translation technologies have advanced significantly, with Google Translate handling more than 100 billion words daily in over 100 languages.

Virtual assistants like Siri, Alexa, and Google Assistant leverage AI to understand and respond to user commands, making voice-based communication more convenient and efficient.

5. Entertainment: 

AI is reshaping the entertainment industry with personalized content recommendations, virtual reality experiences, and computer-generated imagery. It enhances user experiences, facilitates content curation, and enables immersive storytelling.

The global AI in the entertainment market is projected to reach $5.5 billion by 2026, with a CAGR of 25.4% from 2019 to 2026.

AI algorithms are used in content recommendation systems of streaming platforms like Netflix and Spotify, which account for a significant portion of their user engagement and revenue.

AI-powered computer-generated imagery (CGI) has transformed the visual effects industry, enabling the creation of realistic and immersive experiences in movies, video games, and virtual reality.

6. Finance: 

AI is revolutionizing the financial industry with automated trading, fraud detection, risk assessment, and personalized financial advice. It enables efficient data analysis, real-time market insights, and improved decision-making processes.

A report by PwC estimates that AI could contribute up to $15.7 trillion to the global economy by 2030, with the financial sector being one of the largest beneficiaries.

AI-driven automated investment platforms, also known as robo-advisors, managed over $1 trillion in assets globally in 2020.

7. Smart Homes: 

AI-powered smart home devices and virtual assistants, such as voice-activated speakers and smart thermostats, make our daily lives more convenient and efficient. They automate tasks, provide personalized recommendations, and create a connected and intelligent living environment.

The global smart home market is expected to reach $246.97 billion by 2027, with a CAGR of 11.6% from 2020 to 2027.

Voice-activated smart speakers, powered by AI assistants like Amazon Alexa and Google Assistant, have seen widespread adoption. As of 2021, there were over 200 million smart speakers in use worldwide.

8. Manufacturing: 

AI-driven robotics and automation technologies optimize manufacturing processes, increase productivity, and improve product quality. AI-enabled machines and robots perform complex tasks, enhance precision, and enable predictive maintenance.

The global AI in manufacturing market is expected to reach $16.7 billion by 2026, growing at a CAGR of 49.5% from 2019 to 2026.

According to Deloitte, companies that invest in AI and advanced automation technologies in manufacturing can experience productivity gains of up to 30%.

AI-powered predictive maintenance can reduce equipment downtime by up to 50% and maintenance costs by up to 10-40%.

9. Agriculture: 

AI is transforming agriculture by optimizing crop management, monitoring soil conditions, and predicting weather patterns. It enables precision farming techniques, reduces resource waste, and improves agricultural productivity.

The global AI in agriculture market is projected to reach $4 billion by 2026, with a CAGR of 22.5% from 2021 to 2026.

AI-powered agricultural robots and drones are expected to reach a market value of $1.3 billion by 2026.

The use of AI in agriculture can increase crop yields by up to 70%, according to a study by the International Data Corporation (IDC).

10. Cybersecurity: 

AI is strengthening cybersecurity measures by detecting and preventing cyber threats, identifying anomalous behavior, and improving data protection. AI algorithms analyze large datasets to detect patterns and anomalies, enhancing security measures.

According to Gartner, by 2022, 90% of security budgets will be allocated to addressing AI-powered cyber threats.

The global AI in cybersecurity market is projected to reach $38.2 billion by 2026, growing at a CAGR of 23.3% from 2021 to 2026.

In summary: 

AI is transforming every aspect of human life, from healthcare and education to transportation, communication, entertainment, finance, and beyond. Its applications are vast and diverse, revolutionizing industries, improving efficiency, and enhancing the overall human experience. As AI continues to advance, it holds immense potential to shape a future where intelligent technologies seamlessly integrate into our daily lives, making them more convenient, productive, and enriching.

[thehubby]

Taking a Management Information Systems class this semester and nothing prior, not even governmental accounting, has made me just want to give up and go live in the forest as a bearded hermit so much. Take how CEOs were planning to replace employees at least 5 years ago:

Accenture, a technology consulting and outsourcing company, conducted a survey of CEOs in 2018. It found that 74 percent of CEOs plan to use Artificial Intelligence (AI) to automate tasks to a large or very large extent over the next three years. But those same CEOs also believe that only 26 percent of their workers are prepared to collaborate with their AI coworkers. Even worse, only 3 percent of CEOs plan on increasing investments toward training and reskilling employees to prepare them for these new tech-centric jobs.

Or how a typical manager might handle firing an employee due to the impacts of AI:

“Well, I appreciate that attitude, but we’re a small company, really still a startup in many ways. Everyone needs to pull more than their own weight here. Maybe if we were a bigger company, I’d be able to find for a spot for you, see if we could bring you along. But we can’t afford to do that now.” “What about my references?” “I’ll be happy to tell anyone that you’re reliable, that you work 40 to 45 hours a week, and that you’re honest and have integrity.” “Those are important!” “Yes, they are. But today, they’re not enough.”

None of these are criticized; they're just presented as matter-of-fact, or even how things should be in order to run an efficient ship.

I also appreciate the course's implicit suggestion that my chosen field (accounting) is likely to drop in value soon, due to the need for "nonroutine cognitive skills" such as "abstract thinking" and "ability to experiment" -- things that our accounting and ethics classes generally dissuade since attempting to warp bookkeeping principles and tax codes can lead to minor situations like embezzlement and fraud.

In short, you suck, Pearson, and I haven't missed working with you in the two years I was able to avoid it.

[skillzrevo]

Unlock Your Potential with Generative AI, Advanced AI, and Business Intelligence Courses

In a world driven by innovation, skills in Generative AI, Advanced AI, Data Science, and Business Intelligence are your ticket to a future-ready career. With the rapid adoption of AI technologies in India, the USA, and the Middle East, the time to invest in these high-demand fields is now. Whether you’re looking to advance your career, switch industries, or explore new opportunities, learning these skills opens the door to global job prospects and cutting-edge projects.

Why Focus on Generative AI and Advanced AI?

Generative AI has revolutionized industries by enabling machines to generate unique content, automate creative workflows, and develop intelligent tools. By enrolling in a Generative AI course, you’ll learn to work with groundbreaking tools like GPT-4, Stable Diffusion, and more, gaining expertise in creating AI-powered solutions.

On the other hand, an Advanced AI course equips you with technical mastery over machine learning, neural networks, and natural language processing (NLP). These skills are crucial for solving complex challenges and leading AI-powered transformations in any industry.

For those looking to dive deeper, a Master in Generative AI is the perfect way to specialize in this rapidly evolving domain and gain competitive leadership skills.

Global Job Market for AI Professionals

India

AI is transforming India’s economy, with the sector expected to create over 3.5 million AI-related jobs by 2030. From fintech and retail to healthcare and IT, companies like Tata Consultancy Services, Accenture, and Paytm are actively hiring AI specialists. Positions in Data Science, Business Intelligence, and AI start at ₹7 lakh per annum, with experienced professionals earning up to ₹30 lakh annually.

USA

The USA remains a pioneer in AI technology, with the AI market expected to grow at a CAGR of 36% over the next five years. Tech giants like Google, Amazon, and Meta are aggressively recruiting for roles such as Machine Learning Engineer, Generative AI Developer, and AI Architect, with salaries exceeding $150,000 per year. Reports indicate that Generative AI experts are among the top five most sought-after professionals in the USA.

Middle East

The Middle East is rapidly adopting AI to diversify its economies, especially in the UAE and Saudi Arabia. With a projected $15 billion AI market by 2030, industries like oil and gas, logistics, and real estate are leading the way in hiring Business Intelligence Analysts, AI Specialists, and Data Scientists. Starting salaries in the region range from $60,000 to $120,000 per year.

Learning Pathways to Success

Generative AI Courses: Learn how to design and implement AI systems that create text, images, videos, and more.

Advanced AI Courses: Delve into machine learning, deep learning, robotics, and other advanced AI technologies.

Master in Generative AI: Specialize in generative models, their optimization, and real-world applications.

Business Intelligence Programs: Gain expertise in data visualization, reporting tools, and decision-making strategies.

Data Science Certifications: Equip yourself with data analytics, predictive modeling, and machine learning skills.

These programs empower you to work on hands-on projects and gain practical knowledge that employers value.

AI Trends and Opportunities Across Industries

Generative AI in Marketing: AI tools like ChatGPT and DALL-E are transforming content creation, ad personalization, and brand engagement.

Advanced AI in Healthcare: Predictive models are helping doctors diagnose diseases early and deliver personalized treatments.

Business Intelligence in Finance: BI tools are optimizing risk analysis, fraud detection, and investment planning.

Data Science in E-commerce: Data-driven insights are shaping customer experiences and boosting sales strategies.

A LinkedIn report indicates that over 80% of global companies plan to expand their AI teams by 2025, signaling massive hiring opportunities.

Why Choose SkillzRevo?

SkillzRevo offers state-of-the-art programs designed to help learners thrive in AI, data science, and business intelligence. Here’s why thousands of professionals trust SkillzRevo:

Industry-Relevant Content: Courses are curated by AI experts with real-world experience.

Practical Training: Gain hands-on experience with AI tools, datasets, and real-world applications.

Global Certifications: Credentials recognized by top employers across India, the USA, and the Middle East.

Flexible Learning Options: Choose from self-paced, live online, or hybrid programs to suit your schedule.

Career Support: Get access to placement assistance, resume-building workshops, and mock interviews.

Invest in Your Future

The integration of Generative AI, Advanced AI, Business Intelligence, and Data Science is shaping the future of industries worldwide. By acquiring these skills, you can secure a high-paying job, work on transformative projects, and become a leader in the AI revolution.

Take the first step today. Enroll in SkillzRevo’s AI courses and join a global network of forward-thinking professionals shaping the future.

[bobbyyoungsworld]

Top Artificial Intelligence Companies in India: Revolutionizing the Future

Artificial Intelligence (AI) is a driving force in today’s technology landscape, reshaping industries across India. The country has emerged as a hub for AI innovation, with several companies leading the charge in AI development services. In this blog, we’ll explore some of the top AI development companies in India, including ShamlaTech Solutions, a leader in AI agents, chatbots, and generative AI services.

1. Tata Consultancy Services (TCS)

TCS is a pioneer in AI-driven solutions, offering services like cognitive automation, machine learning, and AI integration for enterprises. Their AI platforms are widely used across industries such as healthcare, finance, and retail.

2. Infosys

Infosys leverages AI to drive digital transformation. Their AI platform, Nia, provides automation, analytics, and AI-driven insights, making them a leading AI development company in India.

3. Wipro

Wipro’s AI solutions include HOLMES, an AI and automation platform that enhances business processes, customer experiences, and decision-making capabilities.

4. HCL Technologies

HCL Technologies specializes in AI-powered digital transformation, offering advanced AI tools and services for industries such as manufacturing, healthcare, and banking.

5. ShamlaTech Solutions: Leading AI Development Company in India

ShamlaTech Solutions has established itself as a top-tier AI development company in India, offering comprehensive AI development services tailored to businesses of all sizes. With a strong focus on innovation and customer-centric solutions, ShamlaTech is transforming industries with its cutting-edge AI capabilities.

Key Services:

AI Agents Development: Custom AI agents designed for customer support, virtual assistance, and business automation.

Chatbot Solutions: Intelligent chatbots powered by natural language processing (NLP) for seamless interaction.

Generative AI Services: Innovative solutions that leverage AI to create content, optimize processes, and drive business growth.

Why ShamlaTech Stands Out:

Expert Team: A skilled team of AI developers proficient in the latest technologies.

Tailored Solutions: Customized AI services that meet specific business needs.

Industry Leadership: A proven track record of delivering innovative AI solutions across sectors.

With a commitment to excellence, ShamlaTech Solutions has earned its reputation as a trusted AI development company in India.

6. Tech Mahindra

Tech Mahindra uses AI to drive digital transformation. Their AI solutions include advanced analytics, machine learning, and AI-powered customer engagement tools.

7. Accenture India

Accenture India combines AI with business strategy to offer cutting-edge solutions. Their services include AI-driven automation, predictive analytics, and machine learning applications.

8. Persistent Systems

Persistent Systems specializes in AI-powered digital engineering. Their AI services include cognitive computing, data analytics, and AI integration for enterprise solutions.

9. Mindtree

Mindtree focuses on AI-driven customer experiences and business process optimization. Their AI services include chatbot development, predictive analytics, and AI-powered marketing solutions.

10. Zensar Technologies

Zensar Technologies offers AI solutions that enhance business processes, improve decision-making, and drive innovation. Their AI services span industries like retail, banking, and healthcare.

Why India is a Global AI Hub

India’s AI ecosystem is fueled by a combination of talent, innovation, and government initiatives like Digital India and Make in India. The country’s AI companies are not only catering to local markets but also making a significant impact globally. Companies like ShamlaTech Solutions exemplify India’s leadership in AI innovation, offering world-class AI development services.

Choosing the Right AI Development Company

Partnering with a top AI development company ensures access to state-of-the-art technology and tailored solutions. Companies like ShamlaTech Solutions provide end-to-end AI services, from developing intelligent chatbots to implementing generative AI solutions.

If you’re looking for a trusted partner to unlock the potential of AI for your business, ShamlaTech Solutions is the name to trust.

Ready to transform your business with AI? Contact ShamlaTech Solutions today and discover the power of AI innovation.

[kazifatagar]

Accenture Identifies Trends Shaping Malaysia's Digital Landscape

More than half of Malaysians are now questioning the online content they consume, with 67% prioritizing trust when engaging with a brand, according to Accenture’s Life Trends report. The rise of AI and generative AI has prompted mixed reactions, influencing digital experiences. Accenture Identifies Trends Shaping Malaysia’s Digital Landscape As new technologies reshape lives, people are…

[jcmarchi]

Can I Solve Science?

New Post has been published on https://thedigitalinsider.com/can-i-solve-science/

Can I Solve Science?

A brilliant essay by Stephen Wolfram explores this challenging question.

Created Using Ideogram

Next Week in The Sequence:

Edge 377: The last issue of our series about LLM reasoning covers reinforced fine-tuning(ReFT), a technique pioneered by ByteDance. We review the ReFT paper and take another look to Microsoft’s Semantic Kernel framework.

Edge 378: We review Google’s recent zero-shot time-series forecasting model.

You can Subscribe to The Sequence Below:

TheSequence is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

📝 Editorial: Can AI Solve Science?

Discovering new science is considered by many, including myself, as one of the ultimate tests of AGI (Artificial General Intelligence). We are witnessing glimpses of the potential impact of ‘AI for science’ with models such as those discovering new computer science and math algorithms, or the famous AlphaFold, which is actively used for discovering new proteins.

Is AI going to discover everything?

Can AI help explain the universe?

What are the limits of AI when it comes to science?

There are many theories about the possibilities of AI in scientific domains, but not a formal theory. Last week, computer scientist and physicist Stephen Wolfram published a long and detailed essay attempting to explain the potential and limits of AI in discovering new science. Wolfram’s theory relies heavily on one of his favorite theories: the principle of computational irreducibility.

Wolfram introduced the idea of computational irreducibility in his 2002 book, ‘A New Kind of Science’. This theory also relies on the idea that the universe can be modeled using formal computations. Some of these computations are reducible, which means they allow shortcuts to speed them up, while others do not allow for such flexibility and require executing all the computation steps. Science is possible because, even though many phenomena are computationally irreducible, they contain pockets of reducibility in which patterns can be inferred.

What does this have to do with AI? Well, AI is a form of approximating predictions by inferring regularities in data. In that sense, AI can be applied to solve those pockets of reducibility, but what about the rest? Well, easily, the irreducible parts can be processed using a formal computation language like Wolfram Language (coincidentally 😉).

In summary, Wolfram believes that AI can help advance most scientific workflows, but it will always be limited by the nature of computational irreducibility. In other words, this will prevent AI from autonomously solving science. However, combining AI with computational languages opens the doors to all sorts of possibilities when it comes to advancing science.

Whether you agree with Wolfram’s theory or not, you have to admit that it is certainly interesting. AI, by itself, cannot solve all science, but the combination of AI and computational languages could get pretty far.

📌 Exciting news! The speaker lineup for apply() 2024 is now live.

Join industry leaders from LangChain, Meta, and Visa for insights to master AI and ML in production.

Here’s a sneak peek of the agenda:

LangChain Keynote: Hear from Lance Martin, an ML leader at LangChain, a leading orchestration framework for large language models (LLMs).

Explore Semi-Supervised Learning: Aleksandr Timashov, ML Engineer at Meta, dives into practical approaches for training models with limited labeled data.

Deep Dive into Uplift Modeling: Toyosi Bamidele, Data Scientist at Visa, demystifies uplift modeling for estimating marketing interventions’ impact.

Dive deep into these topics with our expert speakers and gain actionable insights for mastering AI and ML. Stay tuned for the full agenda!

🔎 ML Research

Stable Diffusion 3

Stability AI published a paper outlining the technical details behind Stable Diffusion 3. The paper emphasizes on the rectified flow as a method to improve the mapping between noise and data which is essential to diffusion models —> Read more.

Yi

The team from 01.ai published a paper detailing thearchitecture behind the Yi family of models. Yi is based on 6B adn 34B pretrained models and that further fine-tuned for instruction and chat scenarios —> Read more.

Chatbot Arena

AI researchers from the prestigious LMSys lab at UC Berkeley published a paper detailing the popular Chatbot Arena platform. Chatbot Arena is one of the most popular tools for evaluating and benchmarking foundaiton models —> Read more.

Orca-Math

Microsoft Research published a technical report about Orca-Math, a version of Mistral 7B fine-tuned in mathematical problems. The mode achieved a remarkable 86.8% performance in the GSM8k dataset surpassing models such as LLAMA-270B and GPT-3.5 —> Read more.

Human Level Forecasting with LLMs

AI researchers from UC Berkeley published a study evaluating whether LLMs can forecast events at the level of human forecasters. The evaluation relies on a LLM-RAG system that can collect information, generate forecasts and aggregate predictions —> Read more.

AtP

Google DeepMind published a paper proposing Attribution Patching(AtP) a fast gradient descent method for causal attribution of behavior in LLMs. AtP is a form of activation patching which can identify the modes that lead to false positive predictions —> Read more.

🤖 Cool AI Tech Releases

Claude 3

Anthropic released the Claude 3 model family showcasing impressive performance —> Read more.

Inflection 2.5

Inflection AI unveiled the new version of its marquee foundation model which seems to achieve impressive performance across different benchmarks —> Read more.

Einstein 1 Studio

Salesforce released Einstein 1 Studio, a set of low-code tools for customizing Einstein CoPilot —>Read more.

TripoSR

Stability AI released TripoSR, a model that can generate 3D objects from single images —> Read more.

🛠 Real World ML

Can I Solve Science?

Stephen Wolfram published a long and super insightful essay detailing the history, possibilities and challenges of AI when comes to discover new science. The essay builds on Wolfram;s ideas of computation reducibility and outlines a clear bou`ndary about the areas that “AI in science” is applicable and those in which it isn’t —> Read more.

Python Upgrades at Lyft

The Lyft engineering team discusses their processes for upgrading Python at scale —> Read more.

📡AI Radar

San Altmant rejoined the OpenAI board of directors.

Multiverse Computing raised $27 million to apply quantum computations to AI.

Allen AI’s (AI2) Incubator secured $200 million in compute resources.

Accenture acquired edtech platform Udacity to boost AI education.

Databricks disclosed an impressive $1.6 billion in revenue accelerated by AI.

Andreessen Horowitz is raising two new AI funds.

Accenture and Cohere announced a partnership focused on security in generative AI.

Snowflake and Mistral announced a strategic alliance to enable LLM capabilities in its Cortex platform.

AI agent platform Brevian came out of stealth mode with a $9 million seed round.

OpenAI disclosed a series of emails from Elon Musk that challenge the arguments of the recent lawsuit.

India unveiled some pretty aggresive AI regulations.

Hugging Face is getting into robotics with some big hires.

Data observability platform Metaplane raised $13.8 million in a Series A.

[aitalksblog]

Generative AI: Catalyzing America's Productivity and Economic Growth

(Images made by author) Generative AI stands at the forefront of technological innovation, promising to transform the US economic landscape. Drawing from a recent report by Microsoft and Accenture titled “Unlocking the Economic Potential of the US Generative AI Ecosystem”, this post examines the potential of generative AI to drive unprecedented productivity, foster economic growth, and position…

[global-research-report]

Revolutionizing Workforce Efficiency: The Growing Field Service Management Market

Field Service Management Industry Overview

The global field service management market size is expected to reach USD 11.78 billion by 2030, registering a CAGR of 13.3% from 2023 to 2030, according to a new report by Grand View Research, Inc. Various other factors such as improper management of inventory, increased inventory cycle time, increased holding cost, increased ordering cost and incorrect information about the stock further increase the cost of business operations. FSM software helps to fortify the functionality of the service industry while improving overall profitability.

The main forces which are driving the market include the increase in number of field operations across manufacturing, oil & gas and construction sector., increase in the use of smartphone devices, and rising demand for better organizational efficiency and reduced cost of operations. The advancement of cloud services supports the integration of the cloud to the FSM software. This is expected to surge the FSM market growth over the next nine years. Over the forecast period, most of the end-use industries are expected to deploy the FSM software on the cloud rather than on the premise.

Gather more insights about the market drivers, restrains and growth of the Field Service Management Market

The global field service management market is anticipated to witness high growth over the forecast period. The high presence of smartphones and tablets are playing an important role in the overall growth of the FSM industry globally. FSM solutions are also compatible with next-generation smartphone operating systems, further boosting their importance across the competitive landscape.

Browse through Grand View Research's Communication Services Industry Research Reports.

The Africa roaming tariff market size was estimated at USD 2.36 billion in 2024 and is projected to grow at a CAGR of 5.6% from 2024 to 2030.

The global A2P messaging market size was estimated at USD 71.50 billion in 2024 and is projected to grow at a CAGR of 5.4% from 2025 to 2030.

Field Service Management Market Segmentation

Grand View Research has segmented the global field service management market based on component, deployment, enterprise, end-use and region:

Field Service Management Component Outlook (Revenue in USD Million, 2017 - 2030)

Solution

Mobile field execution

Service contract management

Warranty management

Workforce management

Customer management

Inventory management

Others

Services

Implementation

Training & support

Consulting & advisory

Field Service Management Deployment Outlook (Revenue in USD Million, 2017 - 2030)

On-Premise

Cloud

Field Service Management Enterprise Outlook (Revenue in USD Million, 2017 - 2030)

Large enterprises

SMEs

Field Service Management End-use Outlook (Revenue in USD Million, 2017 - 2030)

Energy & utilities

Telecom

Manufacturing

Healthcare

BFSI

Construction & real estate

Transportation & logistics

Retail & wholesale

Others

Field Service Management Regional Outlook (Revenue in USD Million, 2017 - 2030)

North America

US

Canada

Europe

UK

Germany

France

Asia Pacific

China

Japan

India

Australia

South Korea

Latin America

Brazil

Mexico

Middle East and Africa

Saudi Arabia

South Africa

UAE

Key Companies profiled:

IBM Corporation

Agile 3 Solutions LLC

Accenture

Comarch SA

Salesforce, Inc.

Infor

Klugo Group, SAP SE

Astea International, Inc.

Trimble Navigation Limited

Tech Mahindra Limited

Recent Developments

In September 2022, Tech Mahindra launched YANTR.AI, a new cognitive AI solution that enhances and simplifies field services. The solution is expected to provide actionable insights to enterprises for better planning and execution of field services. It further strengthens Tech Mahindra's Business Process as a Service (BPaaS) portfolio.

In July 2022, Accenture was selected by Hero MotoCorp Ltd. to help the company manage the increasing complexity of its products, markets, and supply chain networks. The program includes planning optimization, supply chain strategy, and logistics enhancement & cost optimization of overall digital supply chain suite.

In October 2021, Opsivity, a field support Software-as-a-Service (SaaS) provider, launched in the U.S. market. The company targets the fast-growing remote field operations sector, needing more skilled field technicians. Opsivity's SaaS solution uses AI and AR to help field technicians solve technical issues faster, increasing productivity in a labor-challenged industry.

In April 2020, IBM launched an equipment maintenance assistant, IBM Maximo, an AI-powered solution that helps organizations improve their asset maintenance program. The solution provides insights into equipment failure patterns and recommends the most effective repair methods. It helps to reduce knowledge gaps and silos within organizations, leading to faster repairs, lower costs, and extended asset life.

In August 2019, Salesforce announced the acquisition of ClickSoftware, a provider of field service management solutions. The acquisition will improve Salesforce Service Cloud by offering clients a more connected and intelligent customer service experience. Salesforce's acquisition of ClickSoftware enabled it to provide its customers with a full field service management solution. It enables firms to improve the efficiency and efficacy of their field service operations, resulting in better customer service.

Order a free sample PDF of the Field Service Management Market Intelligence Study, published by Grand View Research.

[performix]

Generative AI in the USA: Transforming Business in 2024

Generative AI (Gen AI) is reshaping industries across the USA, powering significant advancements in business operations, customer engagement, and revenue growth. Leading companies like IBM, Amazon, and Accenture are pioneering its use, providing powerful examples of how Gen AI can enhance efficiency and competitive advantage. Below, we explore the latest Gen AI advancements and offer strategies for businesses to leverage this transformative technology effectively. 

Latest Gen AI Developments from Industry Leaders 

Accenture’s AI Research 

Accenture’s research reveals that 74% of businesses investing in Gen AI have achieved positive outcomes, showing gains in both revenue growth and productivity. These benefits are especially prominent in companies that modernize processes with AI, although many still face challenges with data quality and skill gaps, which are key to unlocking Gen AI’s full potential. 

Amazon’s Gen AI Applications 

Amazon is integrating Gen AI into logistics and retail operations, using predictive analytics to enhance customer satisfaction through personalized shopping experiences. These innovations have improved both efficiency and sales conversion rates, a model other businesses can replicate to meet evolving customer expectations.

IBM’s Watson with Gen AI 

IBM is enhancing its Watson platform with generative AI capabilities designed for enterprise use. This includes new natural language processing tools that help businesses analyze feedback and streamline operations, demonstrating how custom generative AI solutions can seamlessly integrate with existing business systems. 

Gen AI’s Potential for Startups and SMBs 

The rise of Gen AI is not limited to large corporations. Many small and medium-sized businesses (SMBs) and startups across the USA are adopting Gen AI solutions, particularly in sectors like healthcare, finance, and retail. For SMBs, Gen AI offers opportunities to streamline processes and improve customer experiences, giving them a competitive edge. 

Key Strategies for SMBs 

1. Identify Targeted Use Cases 

SMBs should start by identifying specific applications of Gen AI, such as automating customer service or improving data analysis. 

2. Use Cloud-Based Solutions 

Cloud platforms provide cost-effective access to Gen AI tools, allowing SMBs to adopt without major infrastructure investment. 

3. Train Your Team 

Upskilling employees ensures effective use of Gen AI, maximizing its impact across business functions. 

4. Adopt a Data-Driven Approach 

High-quality data is essential for accurate AI predictions, so SMBs should establish robust data collection and management practices. 

For more insights on how generative AI can enhance your business, explore Performix’s resources on generative AI. 

[govindhtech]

NVIDIA AI Blueprints For Build Visual AI Data In Any Sector

NVIDIA AI Blueprints

Businesses and government agencies worldwide are creating AI agents to improve the skills of workers who depend on visual data from an increasing number of devices, such as cameras, Internet of Things sensors, and automobiles.

Developers in almost any industry will be able to create visual AI agents that analyze image and video information with the help of a new NVIDIA AI Blueprints for video search and summarization. These agents are able to provide summaries, respond to customer inquiries, and activate alerts for particular situations.

The blueprint is a configurable workflow that integrates NVIDIA computer vision and generative AI technologies and is a component of NVIDIA Metropolis, a suite of developer tools for creating vision AI applications.

The NVIDIA AI Blueprints for visual search and summarization is being brought to businesses and cities around the world by global systems integrators and technology solutions providers like Accenture, Dell Technologies, and Lenovo. This is launching the next wave of AI applications that can be used to increase productivity and safety in factories, warehouses, shops, airports, traffic intersections, and more.

The NVIDIA AI Blueprint, which was unveiled prior to the Smart City Expo World Congress, provides visual computing developers with a comprehensive set of optimized tools for creating and implementing generative AI-powered agents that are capable of consuming and comprehending enormous amounts of data archives or live video feeds.

Deploying virtual assistants across sectors and smart city applications is made easier by the fact that users can modify these visual AI agents using natural language prompts rather than strict software code.

NVIDIA AI Blueprint Harnesses Vision Language Models

Vision language models (VLMs), a subclass of generative AI models, enable visual AI agents to perceive the physical world and carry out reasoning tasks by fusing language comprehension and computer vision.

NVIDIA NIM microservices for VLMs like NVIDIA VILA, LLMs like Meta’s Llama 3.1 405B, and AI models for GPU-accelerated question answering and context-aware retrieval-augmented generation may all be used to configure the NVIDIA AI Blueprint for video search and summarization. The NVIDIA NeMo platform makes it simple for developers to modify other VLMs, LLMs, and graph databases to suit their particular use cases and settings.

By using the NVIDIA AI Blueprints, developers may be able to avoid spending months researching and refining generative AI models for use in smart city applications. It can significantly speed up the process of searching through video archives to find important moments when installed on NVIDIA GPUs at the edge, on-site, or in the cloud.

An AI agent developed using this methodology could notify employees in a warehouse setting if safety procedures are broken. An AI bot could detect traffic accidents at busy crossroads and provide reports to support emergency response activities. Additionally, to promote preventative maintenance in the realm of public infrastructure, maintenance personnel could request AI agents to analyze overhead imagery and spot deteriorating roads, train tracks, or bridges.

In addition to smart places, visual AI agents could be used to automatically create video summaries for visually impaired individuals, classify large visual datasets for training other AI models, and summarize videos for those with visual impairments.

The workflow for video search and summarization is part of a set of NVIDIA AI blueprints that facilitate the creation of digital avatars driven by AI, the development of virtual assistants for individualized customer support, and the extraction of enterprise insights from PDF data.

With NVIDIA AI Enterprise, an end-to-end software platform that speeds up data science pipelines and simplifies the development and deployment of generative AI, developers can test and download NVIDIA AI Blueprints for free. These blueprints can then be implemented in production across accelerated data centers and clouds.

AI Agents to Deliver Insights From Warehouses to World Capitals

With the assistance of NVIDIA’s partner ecosystem, enterprise and public sector clients can also utilize the entire library of NVIDIA AI Blueprints.

With its Accenture AI Refinery, which is based on NVIDIA AI Foundry and allows clients to create custom AI models trained on enterprise data, the multinational professional services firm Accenture has integrated NVIDIA AI Blueprints.

For smart city and intelligent transportation applications, global systems integrators in Southeast Asia, such as ITMAX in Malaysia and FPT in Vietnam, are developing AI agents based on the NVIDIA AI Blueprint for video search and summarization.

Using computing, networking, and software from international server manufacturers, developers can also create and implement NVIDIA AI Blueprints on NVIDIA AI systems.

In order to improve current edge AI applications and develop new edge AI-enabled capabilities, Dell will combine VLM and agent techniques with its NativeEdge platform. VLM capabilities in specialized AI workflows for data center, edge, and on-premises multimodal corporate use cases will be supported by the NVIDIA AI Blueprint for video search and summarization and the Dell Reference Designs for the Dell AI Factory with NVIDIA.

Lenovo Hybrid AI solutions powered by NVIDIA also utilize NVIDIA AI blueprints.

The new NVIDIA AI Blueprint will be used by businesses such as K2K, a smart city application supplier in the NVIDIA Metropolis ecosystem, to create AI agents that can evaluate real-time traffic camera data. City officials will be able to inquire about street activities and get suggestions on how to make things better with to this. Additionally, the company is utilizing NIM microservices and NVIDIA AI blueprints to deploy visual AI agents in collaboration with city traffic management in Palermo, Italy.

NVIDIA booth at the Smart Cities Expo World Congress, which is being held in Barcelona until November 7, to learn more about the NVIDIA AI Blueprints for video search and summarization.

Read more on Govindhtech.com