#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.

[differenttimemachinecrusade]

Cloud OSS BSS Market Industry Report: Analysis, Trends, and Growth Factors 2032

Cloud OSS BSS Market was valued at USD 22.0 billion in 2023 and is expected to reach USD 60.8 Billion by 2032, growing at a CAGR of 11.96% from 2024-2032

Cloud OSS BSS Market is experiencing remarkable growth, driven by the increasing demand for digital transformation in the telecom industry. As businesses seek scalable and flexible solutions, cloud-based OSS (Operations Support Systems) and BSS (Business Support Systems) are becoming essential for optimizing operations and enhancing customer experiences. This shift is accelerating the adoption of cloud-native technologies, AI-driven automation, and real-time data analytics.

Cloud OSS BSS Market continues to evolve as telecom operators and enterprises transition from traditional infrastructure to cloud-based frameworks. The rising demand for 5G, IoT, and edge computing is further propelling the need for agile, scalable, and cost-efficient OSS BSS solutions. With cloud-native architectures enabling seamless integration and automation, companies are investing in AI, analytics, and open APIs to drive innovation and efficiency.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/3696  

Market Keyplayers:

Amdocs - Amdocs Billing and Revenue Management

Oracle Corporation - Oracle Communications Billing and Revenue Management

SAP SE - SAP Convergent Charging

Nokia Corporation - Nokia CloudBand

Ericsson - Ericsson Revenue Manager

IBM Corporation - IBM Cloud Pak for Communications

Cisco Systems, Inc. - Cisco Cloud Services Router (CSR) 1000V

CSG International - CSG Billing

Netcracker Technology Corporation - Netcracker Revenue Management

Comarch S.A. - Comarch OSS/BSS Suite

Tata Consultancy Services (TCS) - TCS Digital BSS

Hewlett Packard Enterprise (HPE) - HPE GreenLake

Accenture - Accenture Cloud Services

Fujitsu - Fujitsu Network Function Virtualization (NFV)

Huawei Technologies Co., Ltd. - Huawei CloudCore

ZTE Corporation - ZTE CloudStudio

Openet - Openet Policy Manager

Cerillion Technologies - Cerillion Convergent Charging

Mavenir - Mavenir Cloud-Native BSS

Amdocs Openet - Amdocs Openet Policy Control

Market Trends Driving Growth

1. Shift Toward Cloud-Native Architectures

The adoption of cloud-native OSS BSS solutions is increasing as telecom operators seek agile and scalable systems. These solutions support dynamic service provisioning, automation, and real-time network management, improving operational efficiency.

2. AI and Automation in OSS BSS

Artificial Intelligence (AI) and automation are transforming OSS BSS functionalities. AI-powered predictive analytics, self-healing networks, and intelligent customer support are enhancing service delivery, reducing operational costs, and minimizing downtime.

3. Growth of 5G and IoT Integration

With the rapid expansion of 5G networks and IoT connectivity, cloud OSS BSS solutions are essential for managing complex infrastructures. These platforms enable real-time monitoring, network slicing, and personalized service offerings to support next-generation connectivity.

4. Enhanced Customer Experience through Digital BSS

Cloud-based BSS solutions are improving customer engagement through AI-driven chatbots, self-service portals, and personalized billing. The integration of real-time analytics enables telecom providers to deliver customized service plans and proactive customer support.

5. Open APIs and Interoperability

The demand for open APIs is rising, allowing telecom operators to integrate third-party applications and enhance service innovation. Cloud-based OSS BSS platforms provide seamless interoperability with existing systems, fostering a more agile and collaborative ecosystem.

Enquiry of This Report: https://www.snsinsider.com/enquiry/3696 

Market Segmentation:

By Deployment

Public Cloud

Private Cloud

Hybrid Cloud

Managed Services

By Functionality

Order Management

Inventory Management

Billing and Revenue Management

Customer Relationship Management

Analytics and Reporting

By Organization Size

Small and Medium-Sized Businesses

Large Enterprises

By Industry

Telecommunications

Media and Entertainment

Financial Services

Manufacturing

Healthcare

Market Analysis and Current Landscape

Key factors driving market growth include:

Increasing 5G adoption: Telecom providers are leveraging cloud OSS BSS to manage and monetize 5G networks efficiently.

Rising need for automation: AI-driven solutions are reducing manual processes, improving service reliability, and optimizing resource allocation.

Scalability and cost efficiency: Cloud-native OSS BSS solutions offer reduced infrastructure costs, faster deployment, and enhanced operational agility.

Growing demand for personalized customer experiences: Telecom companies are adopting digital BSS platforms to offer tailored services and optimize revenue management.

Despite significant growth, challenges such as data security concerns, regulatory compliance, and integration complexities remain. However, ongoing advancements in cloud security, AI-driven automation, and hybrid cloud deployments are addressing these challenges.

Future Prospects: What Lies Ahead?

1. Expansion of AI and Machine Learning in OSS BSS

AI-driven insights will continue to revolutionize network operations, enabling predictive maintenance, automated issue resolution, and intelligent customer support.

2. Adoption of Edge Computing for Network Optimization

The rise of edge computing will enhance cloud OSS BSS capabilities, allowing faster data processing, reduced latency, and improved real-time analytics.

3. Evolution of Blockchain for Secure Transactions

Blockchain technology is being explored for secure billing, identity management, and fraud prevention within cloud OSS BSS frameworks.

4. Hybrid and Multi-Cloud Deployments

Enterprises are increasingly adopting hybrid and multi-cloud strategies to enhance flexibility, redundancy, and regulatory compliance while optimizing costs.

5. Advancements in Network-as-a-Service (NaaS)

Cloud OSS BSS solutions will play a crucial role in enabling Network-as-a-Service (NaaS) models, allowing telecom providers to offer on-demand, customizable network services.

Access Complete Report: https://www.snsinsider.com/reports/cloud-oss-bss-market-3696 

Conclusion

The Cloud OSS BSS Market is undergoing a rapid transformation, driven by the increasing need for scalability, automation, and digital innovation. As telecom operators and enterprises embrace cloud-native architectures, AI-driven automation, and 5G expansion, the demand for advanced OSS BSS solutions will continue to grow. Companies that invest in open APIs, edge computing, and blockchain integration will gain a competitive edge in this evolving landscape. With ongoing advancements, the future of cloud OSS BSS promises enhanced operational efficiency, cost savings, and a superior customer experience.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Contact Us:

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Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[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.

[gunnariauvinen]

Trends in Software Development

Technological advancements, global challenges, and shifting workplace dynamics are transforming the software development landscape. As businesses continue to navigate the post-pandemic world, digital transformation has become more than just a trend; it's a critical strategy for survival and growth.

Data highlights the profound shift in corporate thinking. Ninety-one percent of businesses are launching digital transformation initiatives, and 89 percent are adopting a digital-first business strategy. This commitment to technological advancement is reflected in projected market revenues, with estimates showing that the software market will surpass $700 billion by 2025.

Artificial intelligence (AI) and machine learning have emerged as the most significant drivers of innovation in 2024. These technologies are no longer confined to tech giants but are being integrated across industries of all sizes, including start-ups. The AI market is expected to surpass half a trillion dollars this year, with projections indicating it could become a $1.87 trillion industry by 2030. Emerging AI trends include automated machine learning, generative AI, advanced natural language processing, and ethical AI frameworks that aim to build trust between users and technology.

Another transformative trend is the rise of low-code and no-code development platforms. Recognizing the complexities and high costs associated with traditional software development, businesses embrace solutions that democratize app creation. Platforms like Bubble and Adalo allow users to develop applications with minimal coding knowledge. These apps rely on drag-and-drop interfaces and pre-made code blocks, making them easy for creators without coding knowledge or expertise. Reports show that enterprises implementing low-code platforms have universally experienced positive returns on investment, thus demonstrating the promise of these solutions.

Cloud computing remains a critical infrastructure for modern businesses, especially after the widespread adoption of remote work. Although IT spending dropped during the pandemic, cloud spending grew by more than six percent, exceeding $250 billion in revenue. Based on that pattern, companies like Accenture have significantly invested in cloud computing by creating divisions dedicated to cloud migration and development.

Progressive web apps, or PWAs, are gaining traction as businesses seek more efficient, user-friendly digital experiences. These web applications offer the functionality of native apps without requiring users to download anything, which is appealing to users, given their limited smartphone storage. For instance, Starbucks' PWA is almost 99 percent smaller than its iOS, delivering double the daily web orders compared to the latter.

Cybersecurity remains a key concern as ransomware attacks and digital threats evolve. Businesses respond by investing in advanced security measures like cyber insurance and security automation. IBM reports that organizations with fully deployed security automation can potentially save millions of dollars in the event of a data breach.

The emergence of microservices architecture represents another significant shift in software development approaches. Unlike traditional monolithic architectures, where entire applications must be modified for small changes, microservices allow developers to build, manage, and update independent modules to optimize troubleshooting. Therefore, microservices architecture developers enjoy more flexibility.

Distributed computing and serverless computing are also gaining momentum. Companies like Netflix and Spotify use them to process large volumes of data more efficiently. The software development landscape will continue to adapt to rapid innovation, resulting in increased efficiency and a focus on user experience.

[meditechinsight01]

The AI in pharmacovigilance market is expected to grow at a CAGR of 12–15% from 2023 to 2030, driven by the need to automate adverse event data processing, stringent regulatory requirements, advancements in AI analytics, cost reduction benefits, and the increasing use of real-world evidence. These factors reshape pharmacovigilance processes, ensuring faster and more accurate safety assessments. However, high implementation costs and data privacy concerns pose challenges to the market growth.

Artificial intelligence (AI) in pharmacovigilance refers to applying machine learning, natural language processing, and other AI technologies to enhance the monitoring, detection, assessment, and prevention of adverse drug reactions and related issues. It helps streamline the traditionally manual processes involved in pharmacovigilance by automating data extraction, signal detection, and case processing. AI facilitates faster and more accurate analysis of large datasets, ensuring regulatory compliance and improving drug safety. The technology is particularly valuable in managing the complexities of real-world data, including unstructured information from medical records, social media, and adverse event reports.

Download a free sample report now 👉

Growing Volume of Adverse Event Data

The increasing volume and complexity of adverse drug reaction (ADR) data are major factors driving the adoption of AI in pharmacovigilance. With the rise of global drug usage and access to various reporting channels, pharmacovigilance teams are overwhelmed by the sheer amount of structured and unstructured data generated daily. AI technologies, such as machine learning and natural language processing, enable efficient data extraction, deduplication, and classification from disparate sources, such as electronic health records, social media, and clinical trial databases. Automating these processes reduces human errors and ensures faster identification of potential safety signals, allowing quicker interventions. This capability is especially crucial as pharmaceutical companies face stringent timelines to comply with regulatory requirements and ensure public safety. By leveraging AI, the industry can handle data growth while maintaining cost efficiency and precision.

Integration of AI with Real-World Data Analytics

One significant advancement boosting the market is the integration of AI with real-world data (RWD) analytics in pharmacovigilance. RWD, sourced from electronic medical records, wearable devices, and patient registries, offers valuable insights into drug safety and efficacy in real-life settings. AI-powered algorithms can process and analyze these vast datasets to detect adverse drug reactions and patterns that might go unnoticed in clinical trials. Additionally, AI enables the identification of rare or long-term side effects through predictive modeling and signal detection. This integration enhances proactive safety monitoring, improves decision-making, and aids in personalized medicine approaches. As regulators increasingly recognize the importance of RWD in drug safety evaluations, the use of AI-driven RWD analytics has become a transformative force in the pharmacovigilance landscape, offering faster and more accurate results to safeguard patient health.

Competitive Landscape Analysis

The global AI in pharmacovigilance market is marked by the presence of established and emerging market players such as WNS, Accenture Plc, IQVIA Inc, Oracle, PAREXEL International Corporation, Cognizant and Aris Global among others. Some of the key strategies adopted by market players include new product development, strategic partnerships and collaborations, and geographic expansion.

Download a sample report for in-depth competitive insights

Global AI in Pharmacovigilance Market Segmentation

This report by Medi-Tech Insights provides the size of the global AI in pharmacovigilance market at the regional- and country-level from 2023 to 2030. The report further segments the market based on component, deployment and end-user.

Market Size & Forecast (2023-2030), By Component, USD Million

Software

Services

Market Size & Forecast (2023-2030), By Deployment, USD Million

On-premises

Cloud-based

Market Size & Forecast (2023-2030), By End-user, USD Million

Pharmaceutical and Biotech Companies

Contract Research Organizations (CROs)

Others

Market Size & Forecast (2023-2030), By Region, USD Million

North America

US

Canada

Europe

UK

Germany

Italy

Spain

Rest of Europe

Asia Pacific

China

India

Japan

Rest of Asia Pacific

Latin America

Middle East & Africa

About Medi-Tech Insights

Medi-Tech Insights is a healthcare-focused business research & insights firm. Our clients include Fortune 500 companies, blue-chip investors & hyper-growth start-ups. We have completed 100+ projects in Digital Health, Healthcare IT, Medical Technology, Medical Devices & Pharma Services in the areas of market assessments, due diligence, competitive intelligence, market sizing and forecasting, pricing analysis & go-to-market strategy. Our methodology includes rigorous secondary research combined with deep-dive interviews with industry-leading CXO, VPs, and key demand/supply side decision-makers.

Contact:

Ruta Halde Associate, Medi-Tech Insights  +32 498 86 80 79  info@meditechinsights.com 

[marketingbusines]

Global Companies in Bangalore: A Look at Top MNCs

Bangalore, often referred to as the Silicon Valley of India, is home to some of the world's leading multinational corporations (MNCs). The city's dynamic ecosystem, skilled workforce, and advanced infrastructure have attracted numerous global businesses, making it a major hub for technology, finance, and research. From IT giants to financial institutions, MNC Companies in Bangalore have significantly contributed to the city's economy and global reputation.

Why Bangalore is a Preferred Destination for MNCs

Several factors contribute to Bangalore's appeal to multinational corporations:

Talent Pool: The city has a highly skilled workforce, thanks to top educational institutions like the Indian Institute of Science (IISc) and the Indian Institutes of Technology (IITs).

IT and Tech Ecosystem: With a strong IT industry and numerous tech parks, Bangalore is a hotspot for software development and innovation.

Favorable Business Environment: Government policies, ease of doing business, and a startup-friendly culture make Bangalore an attractive destination.

Connectivity and Infrastructure: Well-developed infrastructure, international airports, and excellent connectivity facilitate global business operations.

Top MNC Companies in Bangalore

1. Google

Google, one of the biggest tech companies in the world, has a strong presence in Bangalore. Its research and development center works on innovative technologies, including artificial intelligence, cloud computing, and machine learning. The company offers excellent career opportunities for tech professionals in India.

2. Microsoft

Microsoft has been operating in Bangalore for years, contributing to cloud services, artificial intelligence, and enterprise solutions. The company's India Development Center (IDC) in Bangalore plays a crucial role in software development and global innovation.

3. IBM

IBM is one of the oldest multinational companies in Bangalore. It provides IT services, cloud solutions, and AI-driven business models. IBM’s research lab in the city is among the most advanced in India, focusing on cutting-edge technologies.

4. Accenture

Accenture, a leading IT consulting and professional services firm, has multiple offices in Bangalore. The company provides digital transformation, cloud computing, and artificial intelligence solutions for global clients.

5. Amazon

Amazon has established a major presence in Bangalore, operating in various domains such as e-commerce, cloud computing (AWS), and AI-driven innovations. The company continues to expand its footprint, creating employment opportunities in India.

6. Intel

Intel, a global leader in semiconductor technology, has a massive research and development center in Bangalore. The company focuses on chip design, AI research, and high-performance computing.

7. Dell

Dell has been operating in Bangalore for many years, providing IT infrastructure solutions and cloud computing services. The company’s presence in India contributes to innovation in data centers, networking, and enterprise solutions.

8. Cisco

Cisco, a leading networking and cybersecurity company, has a major research and development center in Bangalore. The company plays a vital role in India's digital transformation and IT security sector.

9. Goldman Sachs

Goldman Sachs has one of its largest offices outside the United States in Bangalore. The company focuses on investment banking, financial research, and technology-driven financial solutions.

10. SAP

SAP, a global leader in enterprise software solutions, has a significant presence in Bangalore. The company develops innovative software applications that help businesses manage their operations efficiently.

Impact of MNCs on Bangalore’s Economy

The presence of MNCs in Bangalore has had a transformative impact on the city's economy:

Employment Generation: Thousands of job opportunities have been created, attracting professionals from across India and the world.

Skill Development: Employees benefit from global exposure and high-quality training programs.

Economic Growth: The influx of foreign investment has contributed to Bangalore's rapid economic development.

Infrastructure Development: Business hubs, IT parks, and better urban infrastructure have emerged due to multinational investments.

Challenges Faced by MNCs in Bangalore

Despite its advantages, Bangalore faces some challenges that impact multinational corporations:

Traffic Congestion: The city's rapid expansion has led to traffic congestion, affecting daily commuting.

Rising Cost of Living: Increased demand for housing and amenities has led to higher living costs.

Competition for Talent: With so many MNCs, companies face intense competition in hiring top talent.

Future of MNCs in Bangalore

The future looks promising for MNCs in Bangalore. The city continues to attract global investments in emerging sectors such as artificial intelligence, fintech, and biotechnology. Government initiatives like "Make in India" and "Digital India" further strengthen Bangalore’s position as a global business hub.

As technology advances and industries evolve, Bangalore will remain a preferred destination for multinational corporations looking to expand their operations in India and beyond.

Conclusion

Bangalore's rise as a global business hub is largely driven by the presence of top multinational companies. From IT giants like Google and Microsoft to financial powerhouses like Goldman Sachs, these companies contribute significantly to the city's economic growth and employment landscape.

[advansappz1]

Generative AI in Healthcare: Revolutionizing Patient Care

Generative AI in healthcare is a transformative force. It promises revolutionary changes in patient care. We know that AI integration in various sectors brings groundbreaking advancements. Healthcare is no exception. Generative AI stands out in healthcare as well. It’s a promising application. 

Generative AI generates new content based on existing data patterns. This ability holds immense potential. Furthermore, It reshapes healthcare delivery. Thanks to the integration of Generative AI and healthcare, patient outcomes have improved worldwide. 

Statistics also underscore the significance of generative AI healthcare. The global market of Generative AI in Healthcare is expected to reach $22.1 billion by 2032, compared to $1.8 billion in 2023. 

What’s more? Accenture says 98% of healthcare providers believe AI advances are bringing a new era of business intelligence.

Considering these statistics, It will bring in a new era of innovation and better health outcomes. In this blog post, we’ll discuss the power of generative AI in healthcare. Furthermore, We’ll explore its many uses in different parts of medical practice.

[davidjason]

Top 10 Research and Development Services Companies in India & USA: Driving Innovation in 2025

Research and Development (R&D) plays a crucial role in driving innovation, improving products, and fostering business growth. Companies that invest in Research and Development Services gain a competitive edge in technology, healthcare, and various other industries. Below, we list the top 10 Research and Development Services companies in India and the Research and Development Services companies in the USA, including Vee Technologies in the first position.

1. Vee Technologies

Vee Technologies leads the way in Research and Development Services, offering advanced solutions in healthcare, IT, and engineering. With cutting-edge technology and a strong focus on innovation, Vee Technologies provides world-class Research and Development Services in India and the USA. The company specializes in AI, data analytics, and next-gen product development, making it the preferred choice for businesses worldwide.

2. TCS Research & Innovation

Tata Consultancy Services (TCS) is a global leader in IT and Research and Development Services. The company focuses on artificial intelligence, cloud computing, and cybersecurity, catering to businesses across various industries.

3. Infosys R&D

Infosys is a renowned Research and Development Services company in India, focusing on automation, blockchain, and digital transformation. With extensive R&D facilities, the company drives innovation in enterprise solutions.

4. IBM Research

IBM is a leading Research and Development Services company in the USA, known for its advancements in AI, cloud computing, and quantum computing. The company continuously invests in next-generation technology solutions.

5. Wipro R&D

Wipro is a global technology leader providing high-end Research and Development Services in cybersecurity, AI, and IoT. It collaborates with major enterprises to drive product innovation and digital transformation.

6. HCL Technologies

HCL Technologies offers extensive Research and Development Services in India with expertise in IT, engineering, and product lifecycle management. The company partners with global businesses to enhance innovation and efficiency.

7. Accenture Labs

Accenture Labs is a top-tier Research and Development Services company in the USA, focusing on AI, blockchain, and immersive technology. The company drives enterprise-level transformation with its R&D innovations.

8. Capgemini Engineering

Capgemini Engineering specializes in Research and Development Services, delivering digital and software engineering solutions to businesses worldwide. The company excels in AI-driven product development and automation.

9. Deloitte Research & Innovation

Deloitte’s Research and Development Services focus on digital transformation, analytics, and business intelligence. The company provides consulting and engineering solutions to major corporations.

10. Cognizant R&D

Cognizant is a leading IT and Research and Development Services company in the USA, offering solutions in AI, cloud computing, and business automation. Its innovation-driven approach helps businesses stay ahead of the competition.

Conclusion

Choosing the right Research and Development Services company is essential for businesses looking to innovate and grow. Companies like Vee Technologies lead the way with cutting-edge solutions, making a significant impact on various industries. Whether you need Research and Development Services in India or the USA, these top 10 companies provide exceptional expertise to help businesses succeed.