AI/ML
Taiwan’s ITRI integrates virtual and real technologies on display at CES 2024
Major international manufacturers such as NVIDIA, Meta, and Microsoft are actively building a new generation virtual ecosystem. With the support of the Industrial Technology Department of the Ministry of Economic Affairs, ITRI (Taiwan’s largest high-tech applied research institutions) has continued to develop an interactive experience that integrates virtual and real, and launched its first interactive experience at the US Consumer Electronics Show (CES 2024).
ITRI announced the introduction of AI-incorporating display and entertainment technologies along with robotics innovations at CES 2024. ITRI presented 10 groundbreaking innovations spanning AI robotics, smart sports, digital health, and AI display and entertainment.
ITRI partnered with Lianjia Optoelectronics, a major automotive LED module manufacturer, to launch a “high-fidelity 3D interactive system ” to seize 3D entertainment business opportunities.
Director of Market Research at the Consumer Technology Association (CTA), Jessica Boothe, praised ITRI’s exhibits for embodying the CES 2024 trends of AI, sustainability, and inclusivity. Expressing her enthusiasm, Boothe highlighted one of the showcased innovations, the Hyper-realistic 3D Interactive System, which was poised to launch a collaboration with Excellence Optoelectronics Inc. (EOI), a prominent automobile LED module manufacturer.
“I must say, very exciting showcase this year. We find everything to be on-trend. The CES 2024 trends were predicted to be AI, sustainability, and inclusivity. And we have all of that right here in your booth,” remarked Boothe. “We’re really excited that ITRI has been here since 2017. As we’re celebrating CTA’s 100-year anniversary, it’s nice to say that we have exhibitors like ITRI coming back every year to CES, and we continue to see ITRI continue to innovate,” she added.
“CES is the most influential tech event in the world, and this is the eighth time ITRI has participated,” said ITRI President Edwin Liu. “To be at CES, we have two main purposes: to showcase ITRI on the global stage and to provide our team with valuable exposure to the latest advancements worldwide. Through CES, ITRI is opening up even more collaboration opportunities, engaging with potential investors, and exploring tech licensing and ventures,” he added.
“ITRI has worked on smart interactive display technology for years, and our collaboration with EOI on the Hyper-Realistic 3D Interactive Display is one of the best successes. This also allows us to strategically deploy diversified product lines in Taiwan, the United States, and Europe,” said President Liu. ITRI also promoted the Institute’s strategic partnerships with Light Matrix and its investor ADATA Technology on iGolfPutter, an intelligent interactive golf simulator. Utilizing Light Matrix’s smart sports training and teaching system called SyncShot360 in iGolfPutter, targeting the global sports technology market. Notably, iGolfPutter has been named by Forbes Magazine as one of the technologies to look for at CES 2024.
EOI Chairman, Dr. Kuohsin Huang, elaborated on their collaboration project with ITRI, stating, “Unlike traditional methods relying on multiple cameras, the Hyper-realistic 3D Interactive System (ChartBox) can generate a personal, interactive 3D digital avatar from a 2D photograph. This 2D-to-3D process integrates various technologies, including real-time image matting, backside model generation, expression changes, natural speech, AI response, and facial recognition.” He added, “Furthermore, its next-generation display technology positions EOI to enter the new market of audio-video entertainment and artistic performances.”
Simon Chen, Chairman of ADATA, emphasized, “Beyond our commitment to providing top-notch memory solutions, ADATA is venturing into cutting-edge sports technology through cross-industry collaboration. Our goal is to offer an optimal training environment for athletes and an innovative experience for spectator sports. Leveraging ADATA’s well-established global distribution channels, we can actively promote Taiwan’s sports industry on the international stage.”
Commenting on iGolfPutter and SyncShot360, Light Matrix CEO Joe Chen said, “The combination of fast 3D modeling, volumetric capture, and virtual-real fusion in the metaverse creates never-before-seen services that the sports and art industry would love. Our volumetric view technology, born out of collaboration with ITRI, allows for a more precise, 360-degree intelligent analysis of golf and other sports. It holds the promise of applications in sporting events and stage performances, setting an excellent foundation for future expansion in the global market.”
From left to right in the above photo are Lin Zhaoxian, vice president of ITRI and director of the International Institute of Obstetrics and gynecology, Liu Wenxiong, president of ITRI, Huang Guoxin, chairman of Lianjia Optoelectronics, and Huang Fangyu, general manager of Lianjia Optoelectronics.
About ITRI:
Industrial Technology Research Institute (ITRI) is one of the world’s leading technology R&D institutions aiming to innovate a better future for society. Founded in 1973, ITRI has played a vital role in transforming Taiwan’s industries from labor-intensive into innovation-driven. To address market needs and global trends, it has launched its 2035 Technology Strategy and Roadmap that focuses on innovation development in Smart Living, Quality Health, Sustainable Environment, and Resilient Society.
Over the years, ITRI has been dedicated to incubating startups and spinoffs, including well-known names such as UMC and TSMC. In addition to its headquarters in Taiwan, ITRI has branch offices in the U.S., Europe, and Japan in an effort to extend its R&D scope and promote international cooperation across the globe. For more information, please visit https://www.itri.org/eng.
References:
ABI Research: Telco transformation measured via patents and 3GPP contributions; 5G accelerating in China
“SK Wonderland at CES 2024;” SK Group Chairman: AI-led revolution poses challenges to companies
On Tuesday at CES 2024, SK Group [1.] displayed world-leading Artificial Intelligence (AI) and carbon reduction technologies under an amusement park concept called “SK Wonderland.” It provided CES attendees a view of a world that uses the latest AI and clean technologies from SK companies and their business partners to a create a smarter, greener world. Highlights of the booth included:
- Magic Carpet Ride in a flying vehicle embedded with an AI processor that helps it navigate dense, urban areas – reducing pollution, congestion and commuting frustrations
- AI Fortune Teller powered by next-generation memory technologies that can help computers analyze and learn from massive amounts of data to predict the future
- Dancing Car that’s fully electric, able to recharge in 20 minutes or less and built to travel hundreds of miles between charges
- Clean Energy Train that’s capable of being powered by hydrogen, whose only emission is water
- Rainbow Tube that shows how plastics are finding a new life through a technology that turns waste into fuel
Note 1. SK Group is South Korea’s second-largest conglomerate, with Samsung at number one.
SK’s CES 2024 displays include participation from seven SK companies — SK Inc., SK Innovation, SK Hynix, SK Telecom, SK E&S, SK Ecoplant and SKC. While the displays are futuristic, they’re based on technologies that SK companies and their global partners have already developed and are bringing to market.
SK Group Chairman Chey Tae-won said that companies are facing challenges in navigating the transformative era led by artificial intelligence (AI) due to its unpredictable impact and speed. He said AI technology and devices with AI are the talk of the town at this year’s annual trade show and companies are showcasing their AI innovations achieved through early investment.
“We are on the starting line of the new era, and no one can predict the impact and speed of the AI revolution across the industries,” Chey told Korean reporters after touring corporate booths on the opening day of CES 2024 at the Las Vegas Convention Center in Las Vegas. Reflecting on the rapid evolution of AI technologies, he highlighted the breakthrough made by ChatGPT, a language model launched about a year ago, which has significantly influenced how AI is perceived and utilized globally. “Until ChatGPT, no one has thought of how AI would change the world. ChatGPT made a breakthrough, and everybody is trying to ride on the wave.”
SK Group Chairman Chey Tae-won speaks during a brief meeting with Korean media on the sidelines of CES 2024 at the Las Vegas Convention Center in Las Vegas on Jan. 9, 2024
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SK Hynix Inc., SK Group’s chipmaking unit, is one of the prominent companies at CES 2024, boasting its high-performance AI chips like high bandwidth memory (HBM). The latest addition is the HBM3E chips, recognized as the world’s best-performing memory product. Mass production of HBM3E is scheduled to begin in the first half of 2024.
SK Telecom Co. is also working on AI, having Sapeon, an AI chip startup under its wing. Chey stressed the importance of integrating AI services and solutions across SK Group’s diverse business sectors, ranging from energy to telecommunications and semiconductors. “It’s crucial for each company to collaborate and present a unified package or solution rather than developing them separately,” Chey said. “But I don’t think it is necessary to set up a new unit for that. I think we should come up with an integrated channel for customers.”
SK Telecom and Deutsche Telekom are jointly developing Large Language Models for generative AI to be used by telecom network providers.
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References:
https://en.yna.co.kr/view/AEN20240110001900320#
https://eng.sk.com/news/ces-2024-sk-to-showcase-world-class-carbon-reduction-and-ai-technologies
SK Telecom inspects cell towers for safety using drones and AI
SK Telecom and Deutsche Telekom to Jointly Develop Telco-specific Large Language Models (LLMs)
SK Telecom and Thales Trial Post-quantum Cryptography to Enhance Users’ Protection on 5G SA Network
Google announces Gemini: it’s most powerful AI model, powered by TPU chips
Google claims it has developed a new Generative Artificial Intelligence (GenAI) system and Large Language Model (LLM) more powerful than any currently on the market, including technology developed by ChatGPT creator OpenAI. Gemini can summarize text, create images and answer questions. Gemini was trained on Google’s Tensor Processing Units v4 and v5e.
Google’s Bard is a generative AI based on the PaLM large language mode. Starting today, Gemini will be used to give Bard “more advanced reasoning, planning, understanding and more,” according to a Google blog post.
While global users of Google Bard and the Pixel 8 Pro will be able to run Gemini now, an enterprise product, Gemini Pro, is coming on Dec. 13th. Developers can sign up now for an early preview in Android AICore.
Gemini comes in three model sizes: Ultra, Pro and Nano. Ultra is the most capable, Nano is the smallest and most efficient, and Pro sits in the middle for general tasks. The Nano version is what Google is using on the Pixel, while Bard gets Pro. Google says it plans to run “extensive trust and safety checks” before releasing Gemini Ultra to select groups.
Gemini can code in Python, Java, C++, Go and other popular programming languages. Google used Gemini to upgrade Google’s AI-powered code generation system, AlphaCode. Next, Google plans to bring Gemini to Ads, Chrome and Duet AI. In the future, Gemini will be used in Google Search as well.
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Market Impact:
Gemini’s release and use will present a litmus test for Google’s technology following a push to move faster in developing and releasing AI products. It coincides with a period of turmoil at OpenAI that has sent tremors through the tight knit AI community, suggesting the industry’s leaders is far from settled.
The announcement of the new GenAI software is the latest attempt by Google to display its AI portfolio after the launch of ChatGPT about a year ago shook up the tech industry. Google wanted outside customers to perform testing on the most advanced version of Gemini before releasing it more widely, said Demis Hassabis, chief executive officer of Google DeepMind.
“We’ve been pushing forward with a lot of focus and intensity,” Hassabis said, adding that Gemini likely represented the company’s most ambitious combined science and engineering project to date.
Google said Wednesday it would offer a range of AI programs to customers under the Gemini umbrella. It touted the software’s ability to process various media, from audio to video, an important development as users turn to chatbots for a wider range of needs.
The most powerful Gemini Ultra version outperformed OpenAI’s technology, GPT-4, on a range of industry benchmarks, according to Google. That version is expected to become widely available for software developers early next year following testing with a select group of customers.
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Role of TPUs:
While most GenAI software and LLM’s are processed using NVIDIA’s neural network processors, Google’s tensor processing units (TPUs) will power Gemini. TPUs are custom-designed AI accelerators, which are optimized for training and inference of large AI models. Cloud TPUs are optimized for training large and complex deep learning models that feature many matrix calculations, for instance building large language models (LLMs). Cloud TPUs also have SparseCores, which are dataflow processors that accelerate models relying on embeddings found in recommendation models. Other use cases include healthcare, like protein folding modeling and drug discovery.
Google’s custom AI chips, known as tensor processing units, are embedded in compute servers at the company’s data center. Photo Credit: GOOGLE
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Competitors:
Gemini and the products built with it, such as chatbots, will compete with OpenAI’s GPT-4, Microsoft’s Copilot (which is based on OpenAI’s GPT-4), Anthropic’s Claude AI, Meta’s Llama 2 and more. Google claims Gemini Ultra outperforms GPT-4 in several benchmarks, including the massive multitask language understanding general knowledge test and in Python code generation.
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References:
Everything to know about Gemini, Google’s new AI model (blog.google)
Google Reveals Gemini, Its Much-Anticipated Large Language Model (techrepublic.com)
MTN Consulting: Generative AI hype grips telecom industry; telco CAPEX decreases while vendor revenue plummets
Ever since Generative (Gen) AI burst into the mainstream through public-facing platforms (e.g. ChatGPT) late last year, its promising capabilities have caught the attention of many. Not surprisingly, telecom industry execs are among the curious observers wanting to try Gen AI even as it continues to evolve at a rapid pace.
MTN Consulting says the telecom industry’s bond with AI is not new though. Many telcos have deployed conventional AI tools and applications in the past several years, but Gen AI presents opportunities for telcos to deliver significant incremental value over existing AI. A few large telcos have kickstarted their quest for Gen AI by focusing on “localization.” Through localization of processes using Gen AI, telcos vow to eliminate language barriers and improve customer engagement in their respective operating markets, especially where English as a spoken language is not dominant.
Telcos can harness the power of Gen AI across a wide range of different functions, but the two vital telco domains likely to witness transformative potential of Gen AI are networks and customer service. Both these domains are crucial: network demands are rising at an unprecedented pace with increased complexity, and delivering differentiated customer experiences remains an unrealized ambition for telcos.
Several Gen AI use cases are emerging within these two telco domains to address these challenges. In the network domain, these include topology optimization, network capacity planning, and predictive maintenance, for example. In the customer support domain, they include localized virtual assistants, personalized support, and contact center documentation.
Most of the use cases leveraging Gen AI applications involve dealing with sensitive data, be it network-related or customer-related. This will have major implications from the regulatory point of view, and regulatory concerns will constrain telcos’ Gen AI adoption and deployment strategies. The big challenge is the mosaic of complex and strict regulations prevalent in different markets that telcos will have to understand and adhere to when implementing Gen AI use cases in such markets. This is an area where third-party vendors will try to cash in by offering Gen AI solutions that are compliant with regulations in the respective markets.
Vendors will also play a key role for small- and medium-sized telcos in Gen AI implementation, by eliminating constraints due to the lack of technical expertise and HW/SW resources, skilled manpower, along with opex costs burden. Key vendors to watch out for in the Gen AI space are webscale providers who possess the ideal combination of providing cloud computing resources required to train large language models (LLM) coupled with their Gen AI expertise offered through pre-trained models.
Other key points from MTN Consulting on Gen AI in the telecom industry:
- Network operations and customer support will be key transformative areas.
- Telco workforce will become leaner but smarter in the Gen AI era.
- Strict regulations will be a major barrier for telcos.
- Vendors key to Gen AI integration; webscale providers set for more telco gains.
- Lock-in risks and rising software costs are key considerations in choosing vendors.
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Separately, MTN Consulting’s latest forecast called for $320B of telco capex in 2023, down only slightly from the $328B recorded in 2022. Early 3Q23 revenue reports from vendors selling into the telco market call this forecast into question. The dip in the Americas is worse than expected, and Asia’s expected 2023 growth has not materialized.
Key vendors are reporting significant YoY drops in revenue, pointing to inventory corrections, macroeconomic uncertainty (interest rates, in particular), and weaker telco spending. Network infrastructure sales to telcos (Telco NI) for key vendors Ericsson and Nokia dropped 11% and 16% YoY in 3Q23, respectively, measured in US dollars. By the same metric, NEC, Fujitsu and Samsung saw +1%, -52%, and -41% YoY growth; Adtran, Casa, and Juniper declined 29%, 7%, and 20%; fiber-centric vendors Clearfield, Corning, CommScope, and Prysmian all saw double digit declines.
MTN Consulting will update its operator forecast formally next month. In advance, this comment flags a weaker spending outlook than expected. Telco capex for 2023 is likely to come in around $300-$310B.
MTN Consulting’s Network Operator Forecast Through 2027: “Telecom is essentially a zero-growth industry”
MTN Consulting: Top Telco Network Infrastructure (equipment) vendors + revenue growth changes favor cloud service providers
Proposed solutions to high energy consumption of Generative AI LLMs: optimized hardware, new algorithms, green data centers
Cloud Service Providers struggle with Generative AI; Users face vendor lock-in; “The hype is here, the revenue is not”
Global Telco AI Alliance to progress generative AI for telcos
Amdocs and NVIDIA to Accelerate Adoption of Generative AI for $1.7 Trillion Telecom Industry
Bain & Co, McKinsey & Co, AWS suggest how telcos can use and adapt Generative AI
Generative AI Unicorns Rule the Startup Roost; OpenAI in the Spotlight
Generative AI in telecom; ChatGPT as a manager? ChatGPT vs Google Search
Generative AI could put telecom jobs in jeopardy; compelling AI in telecom use cases
MTN Consulting: Satellite network operators to focus on Direct-to-device (D2D), Internet of Things (IoT), and cloud-based services
MTN Consulting on Telco Network Infrastructure: Cisco, Samsung, and ZTE benefit (but only slightly)
MTN Consulting: : 4Q2021 review of Telco & Webscale Network Operators Capex
Granite Telecommunications expands its service offerings with Juniper Networks
Juniper Networks today announced that its customer and partner, Granite Telecommunications, a $1.8 billion provider of communications and technology solutions, has expanded its service offerings to include Juniper Networks’ full-stack of campus and branch services, including Wired Access, Wireless Access and SD-WAN, all driven by Mist AI™. This move will enhance Granite’s ability to support its customers’ unique verticals, such as healthcare, retail, education, manufacturing, hospitality and financial.
Granite has been working closely with Juniper for several years, and with this expanded AI-driven enterprise portfolio they now offer Juniper’s full suite of campus and branch networking solutions. By leveraging Mist AI and a single cloud across the wired, wireless and SD-WAN domains, Granite saves time and money with client-to-cloud automation and assurance, while accelerating deployments with Zero Touch Provisioning and automated configurations. In addition, Granite delivers more value to its customers with a broadened service portfolio that offers new highly differentiated services.
“Granite stands as Juniper’s largest AI-Driven SD-WAN partner in Managed Services within the Americas, underscoring the strength of our relationship and confidence in Juniper’s cutting-edge networking technology,” said Rob Hale, President and CEO at Granite. “As we expand our partnership, we are poised to elevate the customer experience to new heights by offering a full suite of Juniper solutions, imbued with the defining qualities of reliability, performance and security that characterize Juniper.”
Granite has been expanding its nationwide support to address the changing and growing needs of its customers. The company is committed to delivering specialized services for the unique requirements of its customers’ verticals. The addition of Juniper’s software-defined branch and wireless services is expected to be a significant benefit to many of its customer sectors. These services are designed to improve the performance and security of networks in various industries and make it easier for businesses to manage their network infrastructure.
“We are very excited to take our relationship with Granite Telecommunications to the next level,” said Sujai Hajela, Executive Vice President, AI-Driven Enterprise at Juniper Networks. “They have proven to be an exceptional partner and leader in the communications industry, who is especially adept at leveraging AI and the cloud to deliver high value managed services to their customers. With the full AI-driven enterprise portfolio, Granite can truly differentiate from their competition with exceptional client-to-cloud user experiences.”
With this expansion, Granite continues to demonstrate its commitment to providing customers with the best possible network experience. The addition of Juniper’s full-stack solutions will enable Granite to enhance its capabilities and better serve its customers, while also providing the company with a competitive edge in the market.
About Juniper Networks:
Juniper Networks is dedicated to dramatically simplifying network operations and driving superior experiences for end users. Our solutions deliver industry-leading insight, automation, security and AI to drive real business results. We believe that powering connections will bring us closer together while empowering us all to solve the world’s greatest challenges of well-being, sustainability and equality. Additional information can be found at Juniper Networks (www.juniper.net) or connect with Juniper on Twitter, LinkedIn and Facebook.
References:
Barriers for telcos deploying AI in order to improve network operations
Communications service providers (CSPs) face a host of barriers, such as accessing high-quality data, that impede thesir ability to effectively deploy AI which could improve network and service operations, according to new research commissioned by Nokia and conducted by Analysys Mason.
“CSPs are unable to access high-quality data sets (which will enable them to make more accurate decisions) because they are using legacy systems with proprietary interfaces. This will restrict how quickly they can integrate AI into their networks,” according to the research, which is based on responses from 84 CSPs surveyed globally.
Almost 50 percent of Tier-1 CSPs ranked data collection as the most challenging stage of the telco AI use case development cycle.
Further, the research found that only six percent of CSPs surveyed believe they are at the most-advanced level of automation, or zero-touch automation, which relies on AI and machine learning (ML) algorithms to manage and improve network operations. The high-quality data issue is also impacting CSPs’ ability to retain AI talent.
Still, 87 percent of CSPs have started to implement AI into their network operations, either as proof of concepts or into production; with 57 percent saying they have deployed telco AI use cases to the point of production.
CSP respondents said they believe AI will help improve network service quality, top-line growth, customer experience, and energy optimisation to meet their sustainability goals.
The research said CSPs should evaluate their telco AI implementation strategies and develop a clear roadmap for AI implementation to overcome their data challenge and other impediments, such as an inability to scale AI use case deployments. The report can be found here.
Adaora Okeleke, Principal Analyst, at Analysys Mason said: “CSPs must transition to more-autonomous operations if they are to manage networks more efficiently and deliver on their main business priorities. But as this research demonstrates, accessing high-quality data remains a critical obstacle to deploying telco AI within their networks. They need to really examine their AI implementation strategies to work around this data quality issue.”
Andrew Burrell, Head of Business Applications Marketing, Cloud and Network Services at Nokia, said: “AI has a crucial role in driving step changes in network performance, including cutting carbon footprints. CSPs are aware of the challenges of more deeply embedding AI into their operations and, as this research points out, the steps they can take to positively alter that situation, including building the right ecosystem of vendor partners with the right skillsets that can better cater to their network needs.”
Resources and additional information:
Webpage: https://www.nokia.com/networks/ai-ops/
References:
TPG, Ericsson launch AI-powered analytics, troubleshooting service for 4G/5G Mobile, FWA, and IoT subscribers
Australia telco TPG Telecom and Ericsson today announced a new multi-year agreement to deliver an Australian-first cloud-native and AI-powered analytics tool to pinpoint and improve mobile network performance for customers. Based on Ericsson Expert Analytics and EXFO Adaptive Service Assurance, the solution gives TPG Telecom’s Technology, Network and Care teams an in-depth, end-to-end understanding of subscriber’s experience at an individual level. Through the new agreement, TPG Telecom will gain insights from its 4G and 5G Mobile, Fixed Wireless Access and IoT subscribers using smart data collection with embedded intelligence to predict, prioritise, and resolve performance issues as they arise in real-time.
These insights will enable TPG Telecom to react quicker to network issues, improve performance and reduce the need for infrastructure-based diagnoses, allowing the telco to enhance its service experience for customers.
The solution integrates Ericsson Expert Analytics, EXFO adaptive service assurance and Ericsson software probes, provided as part of Ericsson’s dual-mode 5G Core, to deliver end-to-end network visibility and reduced total costs.
TPG Telecom is the first in Australia and one of the first communication service providers (CSP) globally to deploy Ericsson Expert Analytics in a commercial network using cloud-native technologies. As a cloud-native software, its embedded scalability, agility and resilience means it is designed to flexibly handle TPG Telecom’s requirements as its network and use-cases evolve, adapting to any unexpected challenges.
TPG Telecom General Manager Cloud/Infrastructure NW Services, Chris Tsigros, said: “TPG Telecom is committed to investing in cutting edge technology designed to provide superior network experience to every single one of our customers. The analytics and troubleshooting solution we’re implementing with Ericsson will help ensure we deliver a great experience for our customers. This new technology will change the way in which the TPG Telecom customer care team interacts with our customers, leading to greater effectiveness and increased customer satisfaction. It’s just another way we’re putting our customers first.”
Emilio Romeo, Head of Ericsson, Australia and New Zealand, says: “Embarking on this multi-year deployment of advanced analytics and troubleshooting capabilities with TPG Telecom further demonstrates our commitment to bringing the best mobile telecommunications experience to all Australians. It is the latest in a long history of working side by side with TPG Telecom to bring groundbreaking technology to Australia and a new level of service experience to the Australian people. With the Ericsson Expert Analytics solution implementation, and the real-time access to the data from the dual-mode 5G Core thanks to its built-in software probes, TPG Telecom can gain greater network visibility at a lower cost, passing on the benefits to its customers as they enjoy its services across the country.”
The initial deployment phase focused on acquiring profound insights and troubleshooting capabilities through the software probes built into Ericsson’s cloud-native dual-mode 5G Core. The state-of-the-art solution delivered to TPG adopts an innovative approach that combines probing and event-based monitoring, ensuring rapid and effective issue resolution.
One of the standout features of this deployed solution is its capacity to provide comprehensive troubleshooting across the entire network, all within a unified application. TPG benefits from a range of advanced functionalities, including On-Demand Troubleshooting and robust filtering capabilities, significantly expediting the identification and resolution of network challenges.
With this implementation, TPG Telecom gains the ability to trace and monitor subscriber sessions handled by the core network, which forms the foundation of TPG Telecom’s mobile network. Currently, the solution successfully monitors approximately 5 million subscribers, and its coverage continues to expand
The full solution will continue to be rolled out in phases of further enhancements, and will give TPG Telecom the ability to automatically detect issues from captured network and subscriber insights. TPG Telecom will also benefit from AI-powered recommendations for correction of any network or customer issues found.
Ericsson Expert Analytics is an open system designed for ease of integration in multi-vendor hybrid environments. The software solution is powered by anomaly detection techniques based on machine learning and artificial intelligence, transforming data at scale into actionable insights for better business outcomes. It is designed and used to analyze the real-time network data of more than 250 million subscribers of mobile telecommunications operators all over the world.
The solution follows the 2021 completion of the virtualisation of TPG Telecom’s core network and a new partnership to deploy Ericsson’s dual-mode 5G Core for standalone 5G networks.
About TPG TELECOM:
TPG Telecom Limited, formerly named Vodafone Hutchison Australia Limited, was listed on the Australian Securities Exchange on 30 June 2020. On 13 July 2020, this newly listed company merged with TPG Corporation Limited, formerly named TPG Telecom, to bring together the resources of two of Australia’s largest telecommunications companies, creating the leading challenger full-service telecommunications provider. TPG Telecom is home to some of Australia’s most-loved brands including Vodafone, TPG, iiNet, AAPT, Internode, Lebara and felix. https://www.tpgtelecom.com.au/
Resources:
Securing 5G experience with software probes
Data and Analytics for better business outcomes
Cloud native is transforming the telecom industry
TPG Telecom and Ericsson announce 5G Core partnership for standalone 5G networks
TPG Telecom’s ground-breaking cloud transformation
References:
https://www.ericsson.com/en/press-releases/7/2023/tpg-telecom-and-ericsson-launch-australian-first-analytics-and-troubleshooting-solution-to-boost-network-performance-for-customers
Cloud Service Providers struggle with Generative AI; Users face vendor lock-in; “The hype is here, the revenue is not”
Global Telco AI Alliance to progress generative AI for telcos
Park Place Technologies on network monitoring, predictive fault diagnosis and repair; Entuity acquisition adds analytics
Bain & Co, McKinsey & Co, AWS suggest how telcos can use and adapt Generative AI
Forbes: Cloud is a huge challenge for enterprise networks; AI adds complexity
Cloud Service Providers struggle with Generative AI; Users face vendor lock-in; “The hype is here, the revenue is not”
Everyone agrees that Generative AI has great promise and potential. Martin Casado of Andreessen Horowitz recently wrote in the Wall Street Journal that the technology has “finally become transformative:”
“Generative AI can bring real economic benefits to large industries with established and expensive workloads. Large language models could save costs by performing tasks such as summarizing discovery documents without replacing attorneys, to take one example. And there are plenty of similar jobs spread across fields like medicine, computer programming, design and entertainment….. This all means opportunity for the new class of generative AI startups to evolve along with users, while incumbents focus on applying the technology to their existing cash-cow business lines.”
A new investment wave caused by generative AI is starting to loom among cloud service providers, raising questions about whether Big Tech’s spending cutbacks and layoffs will prove to be short lived. Pressed to say when they would see a revenue lift from AI, the big U.S. cloud companies (Microsoft, Alphabet/Google, Meta/FB and Amazon) all referred to existing services that rely heavily on investments made in the past. These range from the AWS’s machine learning services for cloud customers to AI-enhanced tools that Google and Meta offer to their advertising customers.
Microsoft offered only a cautious prediction of when AI would result in higher revenue. Amy Hood, chief financial officer, told investors during an earnings call last week that the revenue impact would be “gradual,” as the features are launched and start to catch on with customers. The caution failed to match high expectations ahead of the company’s earnings, wiping 7% off its stock price (MSFT ticker symbol) over the following week.
When it comes to the newer generative AI wave, predictions were few and far between. Amazon CEO Andy Jassy said on Thursday that the technology was in its “very early stages” and that the industry was only “a few steps into a marathon”. Many customers of Amazon’s cloud arm, AWS, see the technology as transformative, Jassy noted that “most companies are still figuring out how they want to approach it, they are figuring out how to train models.” He insisted that every part of Amazon’s business was working on generative AI initiatives and the technology was “going to be at the heart of what we do.”
There are a number of large language models that power generative AI, and many of the AI companies that make them have forged partnerships with big cloud service providers. As business technology leaders make their picks among them, they are weighing the risks and benefits of using one cloud provider’s AI ecosystem. They say it is an important decision that could have long-term consequences, including how much they spend and whether they are willing to sink deeper into one cloud provider’s set of software, tools, and services.
To date, AI large language model makers like OpenAI, Anthropic, and Cohere have led the charge in developing proprietary large language models that companies are using to boost efficiency in areas like accounting and writing code, or adding to their own products with tools like custom chatbots. Partnerships between model makers and major cloud companies include OpenAI and Microsoft Azure, Anthropic and Cohere with Google Cloud, and the machine-learning startup Hugging Face with Amazon Web Services. Databricks, a data storage and management company, agreed to buy the generative AI startup MosaicML in June.
If a company chooses a single AI ecosystem, it could risk “vendor lock-in” within that provider’s platform and set of services, said Ram Chakravarti, chief technology officer of Houston-based BMC Software. This paradigm is a recurring one, where a business’s IT system, software and data all sit within one digital platform, and it could become more pronounced as companies look for help in using generative AI. Companies say the problem with vendor lock-in, especially among cloud providers, is that they have difficulty moving their data to other platforms, lose negotiating power with other vendors, and must rely on one provider to keep its services online and secure.
Cloud providers, partly in response to complaints of lock-in, now offer tools to help customers move data between their own and competitors’ platforms. Businesses have increasingly signed up with more than one cloud provider to reduce their reliance on any single vendor. That is the strategy companies could end up taking with generative AI, where by using a “multiple generative AI approach,” they can avoid getting too entrenched in a particular platform. To be sure, many chief information officers have said they willingly accept such risks for the convenience, and potentially lower cost, of working with a single technology vendor or cloud provider.
A significant challenge in incorporating generative AI is that the technology is changing so quickly, analysts have said, forcing CIOs to not only keep up with the pace of innovation, but also sift through potential data privacy and cybersecurity risks.
A company using its cloud provider’s premade tools and services, plus guardrails for protecting company data and reducing inaccurate outputs, can more quickly implement generative AI off-the-shelf, said Adnan Masood, chief AI architect at digital technology and IT services firm UST. “It has privacy, it has security, it has all the compliance elements in there. At that point, people don’t really have to worry so much about the logistics of things, but rather are focused on utilizing the model.”
For other companies, it is a conservative approach to use generative AI with a large cloud platform they already trust to hold sensitive company data, said Jon Turow, a partner at Madrona Venture Group. “It’s a very natural start to a conversation to say, ‘Hey, would you also like to apply AI inside my four walls?’”
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“Right now, the evidence is a little bit scarce about what the effect on revenue will be across the tech industry,” said James Tierney of Alliance Bernstein.
Brent Thill, an analyst at Jefferies, summed up the mood among investors: “The hype is here, the revenue is not. Behind the scenes, the whole industry is scrambling to figure out the business model [for generative AI]: how are we going to price it? How are we going to sell it?”
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References:
https://www.ft.com/content/56706c31-e760-44e1-a507-2c8175a170e8
https://www.wsj.com/articles/companies-weigh-growing-power-of-cloud-providers-amid-ai-boom-478c454a
https://www.techtarget.com/searchenterpriseai/definition/generative-AI?Offer=abt_pubpro_AI-Insider
Global Telco AI Alliance to progress generative AI for telcos
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Global Telco AI Alliance to progress generative AI for telcos
- Four major global telcos joined forces to launch the Global Telco AI Alliance to accelerate AI transformation of the existing telco business and create new business opportunities with AI services.
- They signed a Multilateral MOU for cooperation in the AI business, which includes the co-development of the Telco AI Platform.
Deutsche Telekom, e&, Singtel and SK Telecom have established a new industry group that aims to progress generative AI. Called the Global Telco AI Alliance, it represents a coordinated effort by these four operators to accelerate the AI-fuelled transformation of their businesses, and to develop new, AI-powered business models.
The Telco AI Platform will serve as the foundation both for new services – like chatbots and apps – as well as enhancements to existing telco services. The alliance members plan to establish a working group whose task will be to hammer out co-investment opportunities and the co-development of said platform.
Members will also support one another in operating AI services and apps in their respective markets, and cooperate to foster the growth of a telco AI-based ecosystem.
As of today, all the operators have done is sign a memorandum of understanding (MoU), under which they pledge to carry out all this work. A signing ceremony took place in Seoul, Korea, and was attended – either in person or virtually – by the CEOs of e&, Singtel and SK Telecom, and Deutsche Telekom’s board member for technology and innovation, Claudia Nemat. The Global Telco AI Alliance will also have to ensure that any AI-based services they develop are capable of accounting for cultural differences. They won’t get very far if their virtual assistants make culturally insensitive recommendations, for example.
The seniority of these signatories represents a strong statement of intent though, and the group said it will discuss appointing C-level representatives from each member to the Alliance.
“In order to make the most of the possibilities of generative AI for our customers and our industry, we want to develop industry-specific applications in the Telco AI Alliance. I am particularly pleased that this alliance also stands for bridging the gap between Europe and Asia and that we are jointly pursuing an open-vendor approach. Depending on the application, we can use the best technology. The founding of this alliance is an important milestone for our industry,” said Claudia Nemat, Board Member Technology and Innovation at Deutsche Telekom.
“We recognize AI’s immense potential in reshaping the telecommunications landscape and beyond and are excited to embark on this transformative journey with the formation of the Global Telco AI Alliance. The alliance signifies a strategic commitment to driving innovation and fostering collaborative efforts. Our shared goal is to redefine industry paradigms, establish new growth drivers through AI-powered business models, and pave the way for a new era of strategic cooperation, guiding our industry towards an exciting and prosperous future,” said Khalifa Al Shamsi, CEO of e& life.
“This alliance will enable us and our ecosystem of partners to significantly expedite the development of new and innovative AI services that can bring tremendous benefits to both businesses and consumers. With our advanced 5G network, we are well-placed to leverage AI to ideate and co-create and are already using it to enhance our own customer service and employee experience, increase productivity and drive learning,” said Yuen Kuan Moon, Group Chief Executive Officer of Singtel.
It is not clear at this stage of proceedings whether the operators plan to develop their own in-house AI assets, or license them from the likes of OpenAI’s ChatGPT, or Google Bard. On the one hand, going with a third party that has done most of the legwork offers efficiencies, but on the other hand, the Global Telco AI Alliance might prefer an AI that specialises in telecoms, rather than a generalist.
Japanese vendor NEC showed earlier this month – with the launch of its own large language model (LLM) for enterprises in its home market – that generative AI isn’t necessarily the preserve of Silicon Valley big tech. It also highlighted the desire to develop localised AI for different languages.
The announcement also doesn’t attempt to grapple with any potential ethical pitfalls that might befall the Alliance. While it’s a fairly safe bet that responsible AI development will be an important consideration, it’s always better when companies make that clear.
Even big tech has come round to that way of thinking, with the launch earlier this week of the Frontier Model Forum. Established by Google, Microsoft, OpenAI and self-styled ethical AI company Anthropic, the group aims to advance the development of responsible artificial intelligence for the benefit of humanity.
References:
https://telecoms.com/522891/telcos-team-up-for-ai-platform-project/
https://telecoms.com/522865/google-microsoft-anthropic-and-openai-launch-ai-safety-body/
https://telecoms.com/522603/nec-launches-its-own-generative-ai/
Bain & Co, McKinsey & Co, AWS suggest how telcos can use and adapt Generative AI
Generative Artificial Intelligence (AI) uncertainty is especially challenging for the telecommunications industry which has a history of very slow adaptation to change and thus faces lots of pressure to adopt generative AI in their services and infrastructure. Indeed, Deutsche Telekom stated that AI poses massive challenges for telecom industry in this IEEE Techblog post.
Consulting firm Bain & Co. highlighted that inertia in a recent report titled, “Telcos, Stop Debating Generative AI and Just Get Going” Three partners stated network operators need to act fast in order to jump on this opportunity. “Speedy action trumps perfect planning here,” Herbert Blum, Jeff Katzin and Velu Sinha wrote in the brief. “It’s more important for telcos to quickly launch an initial set of generative AI applications that fit the company’s strategy, and do so in a responsible way – or risk missing a window of opportunity in this fast-evolving sector.”
Generative AI use cases can be divided into phases based on ease of implementation, inherent risk, and value:
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Telcos can pursue generative AI applications across business functions, starting with knowledge management:
Separately, a McKinsey & Co. report opined that AI has highlighted business leader priorities. The consulting firm cited organizations that have top executives championing an organization’s AI initiatives, including the need to fund those programs. This is counter to organizations that lack a clear directive on their AI plans, which results in wasted spending and stalled development. “Reaching this state of AI maturity is no easy task, but it is certainly within the reach of telcos,” the firm noted. “Indeed, with all the pressures they face, embracing large-scale deployment of AI and transitioning to being AI-native organizations could be key to driving growth and renewal. Telcos that are starting to recognize this is non-negotiable are scaling AI investments as the business impact generated by the technology materializes.”
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Ishwar Parulkar, chief technologist for the telco industry at AWS, touted several areas that should be of generative AI interest to telecom operators. The first few were common ones tied to improving the customer experience. This includes building on machine learning (ML) to help improve that interaction and potentially reduce customer churn.
“We have worked with some leading customers and implemented this in production where they can take customer voice calls, translate that to text, do sentiment analysis on it … and then feed that into reducing customer churn,” Parulkar said. “That goes up another notch with generative AI, where you can have chat bots and more interactive types of interfaces for customers as well as for customer care agent systems in a call. So that just goes up another notch of generative AI.”
The next step is using generative AI to help operators bolster their business operations and systems. This is for things like revenue assurance and finding revenue leakage, items that Parulkar noted were in a “more established space in terms of what machine learning can do.”
However, Parulkar said the bigger opportunity is around helping operators better design and manage network operations. This is an area that remains the most immature, but one that Parulkar is “most excited about.” This can begin from the planning and installation phase, with an example of helping technicians when they are installing physical equipment.
“In installation of network equipment today, you have technicians who go through manuals and have procedures to install routers and base stations and connect links and fibers,” Parulkar said. “That all can be now made interactive [using] chat bot, natural language kind of framework. You can have a lot of this documentation, training data that can train foundational models that can create that type of an interface, improves productivity, makes it easier to target specific problems very quickly in terms of what you want to deploy.”
This can also help with network configuration by using large datasets to help automatically generate configurations. This could include the ability to help configure routers, VPNs and MPLS circuits to support network performance.
The final area of support could be in the running of those networks once they are deployed. Parulkar cited functions like troubleshooting failures that can be supported by a generative AI model.
“There are recipes that operators go through to troubleshoot and triage failure,” Parulkar said “A lot of times it’s trial-and-error method that can be significantly improved in a more interactive, natural language, prompt-based system that guides you through troubleshooting and operating the network.”
This model could be especially compelling for operators as they integrate more routers to support disaggregated 5G network models for mobile edge computing (MEC), private networks and the use of millimeter-wave (mmWave) spectrum bands.
Federal Communications Commission (FCC) Chairwoman Jessica Rosenworcel this week also hinted at the ability for AI to help manage spectrum resources.
“For decades we have licensed large slices of our airwaves and come up with unlicensed policies for joint use in others,” Rosenworcel said during a speech at this week’s FCC and National Science Foundation Joint Workshop. “But this scheme is not truly dynamic. And as demands on our airwaves grow – as we move from a world of mobile phones to billions of devices in the internet of things (IoT)– we can take newfound cognitive abilities and teach our wireless devices to manage transmissions on their own. Smarter radios using AI can work with each other without a central authority dictating the best of use of spectrum in every environment. If that sounds far off, it’s not. Consider that a large wireless provider’s network can generate several million performance measurements every minute. And consider the insights that machine learning can provide to better understand network usage and support greater spectrum efficiency.”
While generative AI does have potential, Parulkar also left open the door for what he termed “traditional AI” and which he described as “supervised and unsupervised learning.”
“Those techniques still work for a lot of the parts in the network and we see a combination of these two,” Parulkar said. “For example, you might use anomaly detection for getting some insights into the things to look at and then followed by a generative AI system that will then give an output in a very interactive format and we see that in some of the use cases as well. I think this is a big area for telcos to explore and we’re having active conversations with multiple telcos and network vendors.”
Parulkar’s comments come as AWS has been busy updating its generative AI platforms. One of the most recent was the launch of its $100 million Generative AI Innovation Center, which is targeted at helping guide businesses through the process of developing, building and deploying generative AI tools.
“Generative AI is one of those technological shifts that we are in the early stages of that will impact all organizations across the globe in some form of fashion,” Sri Elaprolu, senior leader of generative AI at AWS, told SDxCentral. “We have the goal of helping as many customers as we can, and as we need to, in accelerating their journey with generative AI.”
References:
https://www.bain.com/insights/telcos-stop-debating-generative-ai-and-just-get-going/
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