Huawei Carrier Business’ Post

1. Advancements in AI Agents Expected in 2025 Main Idea: AI agents are predicted to be a major focus in the tech agenda for 2025, with significant advancements anticipated. Supporting Details: 🤖Emergence of Step-by-Step Reasoning: The development of step-by-step reasoning approaches, such as those used in OpenAI’s o1 model, is expected to enable AI agents to perform actions like making purchases and scheduling meetings without direct human involvement. 📈Business Integration: Major businesses, including banks, have already integrated AI agents into their workflows. For example, BNY employees are now using LLM-fueled agents to assist with daily tasks. 💻Productivity Gains: The integration of AI agents is expected to lead to substantial productivity gains, with companies like Relevance AI offering digital sales teams that can replace human workers at a quarter of the labor cost. Source https://lnkd.in/e3JTfTUZ

Did you know that 80% of a company’s data is unstructured? Yet, this untapped resource is now becoming pivotal for successful Generative AI implementation. Shamik Ganguli, Associate Partner, IBM, and Manoj Agrawal, Banking Frontiers, at the AI Ascend unconference will delve in on how to harness unstructured data for transformational results. Here’s what they will explore: -Emerging Trends in unstructured data utilization. -Key Challenges businesses face and how to overcome them. -Winning Strategies to leverage unstructured data for scaling AI initiatives. Date: February 7, 2025 Time: 6:30 PM onwards Venue: Taj Santacruz, Mumbai Dive deeper into unstructured data trends: https://lnkd.in/evmKrxrc Shamik Ganguli | Shamindra Basu | Harshil Turakhia | Scindia Balasingh | Brooke Byrne | Ricky Chhajed | Babu Nair | Manoj Agrawal | Kailash Purohit #ScalingAI #BankingFrontiers #IBM

CXOs & CIOs in Financial Services – This One’s for You! Unstructured data is a hidden goldmine for financial institutions, yet many struggle to unlock its full potential. At AI Ascend Unconference, industry experts will break down the challenges and reveal winning strategies to harness unstructured data for AI-driven transformation. If you’re a India based CIO, CFO, CHRO, or senior leader in Banking, Insurance, Lending, Capital Markets, or Fintech, this is a session you can’t afford to miss! Join us on February 7, 2025, at Taj Santacruz, Mumbai, and be part of the think tank to join a curated conversation for shaping the future of AI in financial services. Details in the post below. 📢 Tagging CXOs in my network—let’s connect and collaborate! Check out the details in the post below. #ScalingAI #UnstructuredData #FSIInnovation #DigitalTransformation #AIAscend

So much focus on AI in April 😮 As usual Why ❓ I have 2 reasons: ✔ Product launch of our AI bank clerk on Product Hunt - an advanced LLM model that was developed utilizing modern generative AI capabilities and technologies. ✔ Strategic partnership with Data Monsters (NVIDIA partner) to make our team and expertise stronger. It means that starting from this month I focus not only on simple AI tools and solutions but on complicated turnkey implementations with many “hidden ifs” as well. It is a challenging task but it gives more opportunities to build a stronger team, expand our expertise and learn more from such an amazing partner as Data Monsters. AI solutions and services offered by our company and focused at least on banks and fintech companies will cover more business areas – starting from support to smart process automation. This partnership gives us an opportunity to provide 💯 % turnkey implementations of AI solutions including HW delivery. Start from simple LLMs and continue with complicated AI solutions that will boost your business ❗ DM me to know more about AI and our services for banks and fintechs. Have a nice day 😀 #ai #fintech #bank #gpt #solutions https://lnkd.in/eN56QpV7

Why is GenAI truly transformational and why does it seem to overshadow the rest of AI practices? The main reason is that GenAI democratized the most important component of AI → 𝗗𝗮𝘁𝗮 𝗔𝗯𝘂𝗻𝗱𝗮𝗻𝗰𝗲! Deploying valuable AI models and use cases were limited to a certain kind of enterprise, corporates with massive amounts of data! The biggest candidates were teleco, banking, insurance & major retail. Most other SMBs and corporates fell a little short when it came to the 𝙌𝙪𝙖𝙣𝙩𝙞𝙩𝙮 & 𝙌𝙪𝙖𝙡𝙞𝙩𝙮 of data that they own to gain tangible benefits from employing AI in their business. However, with GenAI, the smallest LLM is pretrained on more data than an average business can generate in its lifetime! A major socioeconomic benefit of this technology is that it fueled the interest of many people (𝑏𝑜𝑡ℎ 𝑡𝑒𝑐ℎ𝑛𝑖𝑐𝑎𝑙 𝑎𝑛𝑑 𝑛𝑜𝑛-𝑡𝑒𝑐ℎ𝑛𝑖𝑐𝑎𝑙) to learn and build skills around the subject of AI. This in turn is building a regional talent hub for a skill of high demand for years to come and acts as a catalyst for innovation and AI products to be homegrown. But “𝘞𝘪𝘵𝘩 𝘨𝘳𝘦𝘢𝘵 𝘱𝘰𝘸𝘦𝘳 𝘤𝘰𝘮𝘦𝘴 𝘨𝘳𝘦𝘢𝘵 𝘳𝘦𝘴𝘱𝘰𝘯𝘴𝘪𝘣𝘪𝘭𝘪𝘵𝘺” Especially for deploying GenAI solutions in enterprises, a wider array of factors needs to have a deeper focus: ➵ 𝗗𝗮𝘁𝗮 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: A new generation of policies on how LLMs interact with corporate data. ➵ 𝗗𝗮𝘁𝗮 𝗶𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆: An LLM is capable to breakdown data into their semantic versions, building them up into their original form can cause hallucinations. ➵ 𝗗𝗮𝘁𝗮 𝗟𝗲𝗮𝗸𝗮𝗴𝗲: LLMs are a huge body of information, we need to make sure that sensitive information is not leaked into this body and so accessible by ungoverned channels. ➵ 𝗔𝗜 𝗘𝘁𝗵𝗶𝗰𝘀: Where is your line in the sand? AI shouldn't be in the fabric of everything we do, AI bias can very much be a poison pill to the business. An approach that I found successful to start dealing with those factors: 1️⃣ Build an AI strategy that is tightly coupled with your data strategy. 2️⃣ Micro experimentations in a controlled space, where inputs and outputs are easily managed. I call it AI Exploration. 3️⃣ Building a use case around winning experiments. 4️⃣ Keep your key results dynamic with research, this field changes every day and new findings can affect your strategy in big ways.

AI is shaking up how telecom networks work—are you ready for it? AI enhances efficiency, using predictive analytics to spot problems before they happen and network automation to streamline operations. Telecoms using AI are seeing serious improvements in how their networks perform and handle day-to-day operations. What AI use cases have you fired up the most? Drop your thoughts in the comments! 👇 #AI #TelecomInnovation #NetworkAutomation #PredictiveAnalytics #WZCNetworking

🚀 Discover how AI is transforming Luxembourg’s industries! From finance to healthcare, explore the profound impact of AI on job dynamics and learn why embracing AI is key to staying competitive in the digital age. Whether you’re a business leader or an individual seeking to future-proof your career, now is the time to embrace AI. Explore the boundless opportunities it offers and embark on a journey of innovation and growth. Don’t miss out on the transformative power of AI! Check out the full article! #AIRevolution #Luxembourg #TechRevolution #HeadlineDiplomat #LUDCI 💼🤖 VassiliaOrfanou.com ludci

AI is definitely transforming the way we think about network management. The ability to use predictive analytics to catch issues before they even happen is a game-changer. It’s exciting to see how network automation is driving efficiency and freeing up time for more strategic tasks. Curious to hear what others think—what AI use cases are you most excited about?

With Growth Of AI In Wealthtech, Need For Accurate Data Rises With #AI changing sectors such as #banking, #wealthmanagement and #financialservices, it is essential that #data is #accurate and #controlled. If "garbage" goes into the system, then the results will be a problem. Joe Stensland, chief executive of BridgeFT, a #technology #architecture firm, writes on how important it is to have #accuratedata at a time when #artificialintelligence is on the march. If AI is only as accurate and useful as available data, then mistaken and partial information is going to be a big problem. https://lnkd.in/gDea-v2g Stephen Harris Philip Harris Tom Burroughes Amanda Cheesley Rachel Fokes Andrew Deane Theodora Viney

What is holding back #AI adoption in IT operations? Our research with EMA shows the complexity of implementation (38%), data integration issues (35%), high costs (34%), and shortage of skilled personnel (32%) as the top four implementation challenges for artificial intelligence in #ITOps. Tell us in the comments below, what’s your biggest obstacle? 🔄 Implementation complexity 🔌 Data integration issues 💰 High costs 👥 Skills shortage Learn the rest of the challenges (hint: they *might* not be what you think they are): https://ow.ly/tWjj50Ur195