Sreedhar Rao

Germany is giving the CCP five more years to irrevocably backdoor its telco systems before pulling the plug on Chinese technology. That is the message being sent out by its leaders this week. Despite more than a decade of warnings from the UK, USA and others about the risks of including Chinese technologies in its critical infrastructure systems, Berlin is finally waking up to the reality that any Chinese manufacturer can at the will of the CCP state, be told to implant 'back doors' or 'kill switches' in its technologies for use by the Chinese state in times of war of escalations of tensions with other countries. And China under Xi Jin Ping has been steadily escalating tensions with nearly every country outside of the China since 2012 or 2013. During the next five years, Germany will phase out components made by Chinese companies Huawei and ZTE from its 5G wireless network. This will likely worsen its already strained ties with the second-largest economy in the world, which may further strain its relations with Germany. According to the German Interior Ministry (BMI), by the end of 2026, components made by Chinese technology companies such as Huawei and ZTE will not be allowed to be used in the construction of the country's next-generation 5G mobile networks made by the German industry. To comply with this decision, the BMI decided that all existing components must be replaced by the year 2029. Considering 5G networks as a critical infrastructure, the German government maintains that they will have a key role to play in the energy, transportation, health care, and finance sectors in the coming years. A statement made by Huawei has been issued to CNN, stating that there has been no evidence or scenario that explicitly illustrates that its technology poses any security risks. https://lnkd.in/g4yrZ2f2

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I love this article on how Amazon Web Services (AWS) is approaching Generatuve AI. In the theory of Hierarchy - as systems evolve and commoditize, they become reliant on the organization of the sub-systems. Applied to Generative AI, we now see AWS building out these sub-systems or primitives. These composable assets are the raw materials that allow companies to build at pace and execute effectively. Speed is critical in this environment - but speed is not preordained- it’s a choice. That’s why 10s of thousands of Enterprises are choosing to build with AWS. #Buildon https://lnkd.in/ggzwHBKN

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Just when you think we are getting used to the steady improvements of the capabilities of the LLMs, especially the foundation models – this happens; Anthropic releases Claude 3.5 Sonnet. The week has already been buzzing with various benchmarks, tests and stories about Claude 3.5 Sonnet, but the one that I found stands out is the quality of code generation and the HumanEval benchmark. The HumanEval benchmark contains 164 programming challenges which are handcrafted with 7.7 tests per problem. Claude 3.5 Sonnet scores 92% at the HumanEval benchmark (0-shot)!! Also, another significant one is the GPQA 5-shot benchmark. GPQA is the Graduate level Google-Proof Q&A benchmark, which contains 448 multiple-choice challenging questions. Claude 3.5 Sonnet scored 67.2% !  Just for comparison – expert in-domain PhDs score 65%. This has led to update Alan’s conservative countdown to AGI at 75% !! One step closer to AGI ? Keeping the seatbelts tightly fastened. https://lnkd.in/ebzPfwMu

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The Promises And Risks Of 5G Enterprise Transformation https://lnkd.in/gkF6F79X #enterprise #technology #5G #digitaltransformation #risks #innovation #industry #VR #IoT #networktechnology #datanetwork #security

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Hallelujah! Diana Goovaerts and Elizabeth Starr Miller Coyne of Fierce Network just reported from #DTW24 that AT&T's Yigal Elbaz said he's "looking for vendors to build technology that can be managed #holistically as part of a #horizontal layer in the technology stack rather than overseen as individual verticals." https://lnkd.in/eaTmz74a Excuse me, but I'm going to take a bit of a bow here. EnterpriseWeb has been promoting and demonstrating horizontal architecture for network and service management since 2013 when we led the 1st ETSI #NFV proof-of-concept, as well as the 1st ETSI #ZSM poc in 2016. Our #nocode platform with it's harmonized, standards-based Telco #knowledgegraph model helped win six consecutive TM Forum catalyst projects, with AT&T championing several of them. In 2022 we won a Fierce Telecom award for an Intel #5G #MEC testbed demonstrating a "super" SMO that worked across the #RAN, #Core and #Transport and between layers 1-7 so it could dynamically configure and continuously optimize slices, services and functions to maintain low latency and energy consumption at 50Gbps. In May of 2023 we premiered #Telcograde #GenAI for #intentbased #orchestration with Microsoft demonstrating how a developer can talk to the network to design, deploy and manage complex services. At #MWC24 we demonstrated how the same natural language interface could be used as an abstraction across a set of #CAMARA #APIs. It's been a year and no telecom vendor has replicated these capabilities or matched our performance. I was beginning to think I might have to bleed on stage for the #Telecom industry, but I now have hope. The industry might just have finally had enough with its manually-integrated, tightly-coupled, bloated and brittle silos, which hold back #automation and #AI initiatives. The future is here folks... no need to wait. Here are a few links - Blog "Abstraction for Interoperability and Automation": https://lnkd.in/e6uD4sYB MWC24 demo with RedHat and Microsoft "GraphOps for the AI-enabled Telco": https://lnkd.in/e27kFS-h MWC24 demo with Intel, Microsoft and Fortinet "Dev-centric Networking with CAMARA APIs": https://lnkd.in/ekQD3Sgw MWC24 interview on TheCube with RedHat - https://lnkd.in/dsFyrx-D

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This week marks a pivotal shift for the entire PC value chain from chip to OS to device to cloud to consumer. 💻Microsoft announces CoPilot+ PCs which we believe is a step change for the entire PC industry. 💻Adding CoPliot+ (on device AI) on one end and rearchitecting the Windows ground up and further optimized with advanced chipset solutions on the other end, will completely redefine the PC experience 💻These new GenAI based experiences will warrant advanced configurations from compute (40TOPS NPU min) to memory (16GB+256GB) to support native gen AI-capable features baked in with CoPilot+ Pavan Davuluri: “We're weaving AI through every layer, from chip, to system, to cloud.” 💻Some of the cool features we got a glimpse of: ✨Recall - Recall includes a timeline interface that lets you scroll back in time to go through your search results More than 40 models (LLMs, SLMs) running in background, and this requires high performing and efficient compute. Recall is the best tool for Microsoft to tool on-device AI and personalize and contextualize your use. This is key!! ✨Live Captions : Realtime language translations ✨CoCreater: AI powered image based on sketch or artwork, very powerful for brainstorming ✨Super Resolution: To upscale all photos using AI ✨Adobe: All flagship apps designed to integrate with CoPilot Plus ✨Blackmagic Design Davinci, CapCut Cephable LiquidText and multitude of native apps coming enhanced with CoPilot+ These Gen AI features run multiple AI data models in real-time on the device, enhancing privacy, security, and personalization—key differentiators from earlier AI features that required cloud connectivity. 💻Qualcomm years of investment in low-power AI engines, Arm based designs, to acquisition of NUVIA Inc and integrating all the IP, mobile expertise into a world-class differentiated AI PC platform with Snapdragon X Elite series is helping Microsoft make this happen. 💻How significant this is for Qualcomm is evident from the fact that at the CoPilot+PC launch the world's leading seven PC OEMs launching more than 20+ SKUs entirely on Snapdragon X Elite platforms with Intel Corporation and AMD yet to announce and will follow to further catalyze this step change in the PC industry. 💻The new Microsoft Surface lineup, Samsung Electronics GalaxyBook lineup entirely on Snapdragon X is a proud moment for the Qualcomm team! 💻The performance benchmarks (+58% faster MacBook Air M3) for Snapdragon X Elite are definitely encouraging which are already efficient leveraging Arm, in a sense these first gen AI PCs should be way ahead of x86 based devices. 💻Look forward to Intel Corporation and AMD upcoming designs and Apple with powerful M4 to reinvigorate the market. 💻Counterpoint Technology Market Research estimates 3 out of 4 PCs to be shipped in 2027 will be capable of running Gen AI models and applications natively More insights below: #AI #generativeAI #PCs #Microsoft #Snapdragon #WindowsonArm

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Still working on dual queue low latency networking trials in Comcast's Xfinity Internet network - which has been fun. 🙂 With the FCC's net neutrality rule making coming to a close soon, I found it really interesting to note that our field trial was noted in the order - in Section 514, footnote 2030. "...see also Letter from Prof. Barbara van Shewick...citing Comcast’s low-latency DOCSIS field trials as an example of an innovative service offered over BIAS that is application agnostic, end-user controlled and paid, and that protects the quality of the default BIAS service)." Slides at https://lnkd.in/guEiMXid I am today updating my associated Internet-Draft at https://lnkd.in/gykNDnhf #LowLatency #Latency #L4S #NQB #Bufferbloat #IETF #FCC #NetNeutrality

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Responding to a great question from Dr Nicolas Figay, HDR on another thread, where he objected to my suggestion that #Graphdatabases (#triplestores #RDF #LPG) are sub-optimal for real-time contextual #automation for complex, distributed domains such as #Telecom operations. I wrote about this previously - https://lnkd.in/eVaWZjAU and https://lnkd.in/eVyTu3Rc. Graph database folks have 20+ years vested interest in a very specific technology implementation. If you have a hammer, every use case looks like a nail. However, there is debate in the graph community and Dr. Figay is a thought-leader. I come to this debate from the business operations perspective to enable context-aware intelligent and autonomous systems. The distinction re: graphs is technical, but I'll attempt to be clear in my responses: 1) graph-based technology is critical to many transformational use cases, yet it is poorly understood; 2) many #Telcos and enterprises I work with were oversold on GraphDBs and presumed real-time operational use that they haven't realized; 3) comparing related, but disparate graph technologies objectively clarifies their relative use cases, which is helpful - I don't dismiss GraphDBs; 4) while triples are #deterministic facts, the primary use cases for GraphDBs are #probabilistic for data science, data analytics and recommendations - not real-time (sub-second to 1-2 seconds) contextual automation; 5) a database offering an #OLTP interface is not novel, nor does it make a GraphDB an "automation system" (after all, they are databases by definition); 6) Triple stores support two-dimensional graphs (triples model binary pair relationships between facts and data objects/entities) - they don't model complex functions or workflows, policies, temporal history, software contracts, etc. that are central to automation domains; 7) #Hypergraphs are designed for complex, multi-dimensional and conditional relationships and can model complex, distributed systems; 8) Semantic Web is 1st Order Logic, it aligns with #Prolog / #Datalog languages, which are analytical in nature, not #FunctionalProgramming and #Metaprogramming, which support Higher-Order Logic for general programming languages for application behavior; 9) Hypergraphs can model data and code; 10) Metaprogramming languages (considered the original #AI going back to 1953) are homoiconic, code is data, and is a 1st class citizen of the language, which enables software reflection and deep recursion, to evaluate code at run-time; 11) EnterpriseWeb brings together agents, hypergraphs and stateless functions with metaprogramming techniques to enable a new-class of context-aware systems; and 12) since higher-order languages can raise abstractions over lower-level languages, EnterpriseWeb can import RDF and LPG logical models. I hope that's clear. I'll happily respond to thoughtful comments.

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We are very excited to announce the release of Calico 3.28 which the community has been looking forward to. TL/DR 1. A new Grafana dashboard that helps you monitor Calico Typha’s performance and troubleshoot issues. 2. Calico eBPF dataplane IPv6 is now GA. It supports true IPv6-only clusters as well as dual-stack clusters. 🐝 3. Optional Pod startup delay to ensure networking is up in high-churn scenarios. 4. Tigera operator now supports multiple IP pools, IP pool modification, affinity for operator pods, priorityclassname, and more! 5. Improved policy performance in both eBPF and iptables. 6. Calico now ships with a pprof server. Activate the performance server for real-time views of Typha and Felix components and real-time debugging. A link to this blog is available in the comments section. ———— Tigera - Container Security with built-in network security #CNAPP #zerotrust #cloudnative #Kubernetes #containersecurity #cloudsecurity #eBPF #Istio #OpenShift #Rancher #AWS #Azure #GCP #Fortinet #PaloAltoNetworks #Zscaler #CrowdStrike #SentinelOne #EKS #AKS #GKE #Anthos #RedHat #Devops #SRE #Containers #GenerativeAI  

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Mastering O-RAN RIC: Key Considerations for AI/ML Model Selection When developing an application for a specific use case on O-RAN's RIC platform, keep two key points in mind. ◼ First, select the appropriate AI/ML model. Your choice between a simple model and a more sophisticated one, like deep learning, should depend on your goals and the specific environment (refer to the table below). Additionally, you can leverage AutoML tools. AutoML explores a variety of machine learning algorithms and model architectures, employing techniques such as Bayesian optimization, genetic algorithms, or reinforcement learning to identify the top-performing models. Example Scenario: - Scenario: High Variability and Complexity Data: Large, sequential datasets with non-linear patterns. Resources: Ample computational power and storage. Requirements: Real-time adaptation and low latency inferences. Choice: Deep Reinforcement Learning (DRL) with RNN/LSTM. This setup can learn from real-time data and adjust policies dynamically, handling complex patterns in user behavior and traffic conditions. - Scenario: Stable and Predictable Environment Data: Moderate-sized, non-sequential datasets with linear patterns. Resources: Limited computational power. Requirements: High interpretability and quick implementation. Choice: K-Means Clustering or Logistic Regression. These models are easy to implement, require fewer resources, and provide clear insights into user behaviors and traffic patterns. By carefully considering these criteria and conditions, you can select the most appropriate machine learning model for, for example, traffic pattern recognition in your specific O-RAN network use case. ◼ Second, remember that what you are developing is an independent piece of software, comprising an algorithm and one or more AI/ML models. While you can utilize modules and RIC SDK libraries from xApps and rApps, you have the flexibility to use different types of models in your software. For instance, it's common to have multiple models in your software, for example, a time series model for traffic prediction and a reinforcement learning model (or policy) to make decisions based on those predictions. The key advantage of having a O-RAN ALLIANCE RAN Intelligent Controller (RIC) is the ability to efficiently manage and optimize the radio network. By leveraging open interfaces and r/xApps, O-RAN facilitates the implementation of customized algorithms for specific applications. The O-RAN ALLIANCE outlines various use cases and establishes a policy framework to control the algorithms supporting these use cases. The whitepaper by Rimedo Labs provides an overview of the Traffic Steering use case within the O-RAN framework. It details the use case requirements, the operation of O-RAN nodes with specified interfaces, and the scenario as outlined in the O-RAN ALLIANCE specifications. #ORAN #OpenRAN #ORANRIC #TrafficSteering #AutoML #ModelSelectionCriteria #RICUsecases

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Retrieval-augmented generation is a powerful technique to build enterprise conversational applications, and it has spread like wildfire. However, optimizing cost and performance can be tricky. In this post, written with our friends at Intel AI, you will learn how to quickly build cost-efficient RAG applications with Hugging Face models, the newly launched Open Platform for Enterprise AI (OPEA, https://opea.dev), and the Intel Gaudi 2 accelerator. Code and benchmark included 😀 https://lnkd.in/evFyDf_5 #ai #opensource

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Great article and insights on hybrid approach to LLM, distributed between cloud and edge. (courtesy David Linthicum InfoWorld). We at Arrcus, Inc. share this vision and have the next gen networking architecture to support this Hybrid AI-Cloud. Check out: https://lnkd.in/gGx47izh "Partitioning generative AI LLMs across the edge and central/cloud infrastructures epitomizes the next frontier in AI deployment. This hybrid approach enhances performance and responsiveness and optimizes resource usage and security."

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https://lnkd.in/gCVtzeWc A new milestone in Quantum Computing - may have far reaching impact both for Quantum Security and the future of AI/ML workloads. #5g #6g #quantum #software #innovation

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This is a good one from my colleague Ron Westfall: making radio-area networks, so critical to modern user experiences and yet so unappreciated, more reliable and performant

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What new questions can we ask? What answers do Large Language Models enable? 'How large language models enable network analysis' - a conversation with Sven Sewitz and Elizabeth Press from D3M Labs.🚀 Most organizations are still in the "Awareness" phase, where according to Gartner, interest in AI is sparked. Some advanced organizations have moved to the "Active" phase, where there are proof of concept projects, but those are few and far between. While infrastructure and tool chain remain barriers to feasibility 🚧, the questions persist: 🤔 What new inquiries can we make? How will this impact the culture and organization of data teams and their organizations? 🌐 Introduction: How did Sven become a computational biologist and what does a computational biologist do? 1:50 What is network analysis and why do you think it will be a new paradigm going forward? 3:17 Why are large languages an enabler to network analysis? 5:17 What are hurdles to implementing large language models for network analysis in an actual company? 7:32 There is a large amount of infrastructure investments that are crucial. What are some steps that companies can take? 9:04 Data education and cultural aspect that has to change. What new questions can you now ask? 9:52 How can organizations start along the journey? Follow D3M Labs to continue the conversation. Subscribe to the D3M Labs YouTube Channel. https://lnkd.in/e5Ms-sKt

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Here’s another great piece to add to your summer reading list: floLIVE ’s 2024 Midyear Review. Rony Cohen unpacks 3 key points: Artificial Intelligence and the Role of Data The Chipset Race and the eUICC and iSIM Impact Subset Connectivity Technologies: Cat 1bis and 5G RedCap Let’s dive right in: https://hubs.li/Q02CMVft0 #MidyearReview #IoT #Technology #AI

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If you are an ISP or otherwise a provider of Internet services, you should be aware of a forthcoming publication in the Federal Register, and be prepared to comment on it as appropriate – "In this document, the Federal Communications Commission (Commission) seeks to increase the security of the information routed across the internet by proposing certain reporting obligations on providers of broadband internet access service (BIAS providers) and their use of the Border Gateway Protocol (BGP). Internet traffic can be disrupted, intercepted, and blackholed—when a service provider drops traffic addressed to a targeted IP address or range of addresses by redirecting it to a null route—due to either accidental or deliberate adversarial manipulation of security vulnerabilities inherent to BGP. Together, the intended effect of the plans, filings, and measures the Commission proposes would be to mitigate such threats. BIAS providers would be required to develop BGP Routing Security Risk Management Plans that describe their plans for and progress in implementing security measures that utilize the Resource Public Key Infrastructure (RPKI)." https://lnkd.in/eZGkFH35

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