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[govindhtech]

AMD Infinity Guard, BeeKeeperAI Collaborate Secret Computing

AMD Infinity Guard

The prevalence of ransomware attacks and data breaches in recent years has made it difficult for important business sectors to collaborate. Reports state that organizations are unable to work with suppliers who are attempting to develop potentially ground-breaking apps or discoveries due to the risk posed by threat actors. To keep up the strict restrictions necessary for specific data sets, some businesses don’t even share data within. Researchers’ failure to obtain vital data impedes their capacity to conduct significant study in a number of fields, including government, banking, and healthcare.

Healthcare AI acceleration via a safe platform for algorithm creators and data custodians to collaborate

Data is Never Exchanged or Viewed

The data steward’s safe, HIPAA-compliant environment is where the data is never removed.

Processing Real-World and Protected Data

Employs primary data, which comes directly from the source, as opposed to artificial or de-identified data. Every time, the data is encrypted.

Never Is Intellectual Property Seen or Shared

The algorithm is always encrypted, both when it is uploaded to EscrowAI and when it is moving through the container to the data steward and inside the protected environment of the data steward.

Technology with Secure Enclaves

EscrowAI uses secure enclave technology to reduce the possibility of algorithm IP questioning and data exfiltration during computing.

Matchmaker and intermediary

BeeKeeperAI reduces the time, effort, and expenses of data projects by more than 50% by serving as a matchmaker and broker between data stewards and algorithm developers.

Alan Czeszynski, an expert in the security industry and the marketing and product development leader at BeeKeeperAI, was gracious enough to join me on the AMD EPYC TechTalk podcast series following the Confidential Computing Summit industry gathering in San Francisco. They talked about the state of security and how there has never been a greater need for better hardware and software safeguards.

BeeKeeperAI

EscrowAI, a technology that combines private and confidential computing technology to allow software developers, data scientists, and data owners to collaborate in trusted execution environments (TEE), is utilized by San Francisco-based BeeKeeperAI.

The technology of BeeKeeperAI ensures that an owner always has control over their data. In addition to offering end-to-end encryption and algorithmic and model encryption to safeguard intellectual property, BeeKeeper also applies the algorithm to the data. The business establishes a TEE in a cloud data storage environment after an algorithm is prepared to run against data. Consequently, the data is cut off from all stakeholders, including BeeKeeperAI, the cloud service provider, the data owner, and the owner of the algorithm.

Nobody can see what goes on within the TEE; everyone can only access the output to which they are legally permitted.

“Bring these parties together to enable development and testing of artificial intelligence and machine learning models,” according to Alan, is made possible by BeeKeeper’s secure environment.

Big large language models (LLMs) and generative AI have gained popularity, and as a result, businesses are now more conscious of the need to secure AI, according to Alan. Protecting every stage of the AI and machine learning lifecycle has received a lot of attention lately. According to Alan, this is one of the reasons private computing is starting to get a lot of traction.

Alan warns that legacy security solutions might not provide enough protection in the AI era. The problem with LLMs is that they essentially turn into enormous repositories of all your secrets if you wish to locally train them on your own data,” he continued.

While CISOs and IT administrators prioritize data protection, business managers and data scientists frequently place greater importance on obtaining the data required to develop models that improve the company. Alan claimed that it is far too common for the procedure of obtaining private, protected data to be difficult, costly, and time-consuming. He described a few of the intricate details.

It is usually necessary for parties to have detailed, extremely formal data-use agreements in place. There are often several restrictions on how the data can be interacted with. Audits have to be done, and they always have to. BeeKeeperAI eliminates the effort by offering a technical answer to many of these security challenges.

“Their goal is to eliminate that from the end user and basically take it upon selves,” Alan stated. “The platform then allows the true value, which is basically secure collaboration, getting access to the data, developing your models, being able to execute your AI, ML lifecycle in a secure environment.”

Alan acknowledged that the security features incorporated by AMD EPYC CPUs had strengthened BeeKeeperAI’s offerings. AMD Infinity Guard includes these technologies, such as Secure Encrypted Virtualization and Secure Nested Paging, or SEV-SNP. They prevent the contents of a virtual machine’s memory from being accessed by other VMs operating on the same system or the server they are operating on.

Alan also mentioned adaptability, which is another significant advantage of AMD EPYC. AMD have to provide [clients] a variety of possible platforms, and EPYC is a fantastic one,” said Alan. “In those situations, the safe paging feature of encrypted virtualization and secret containers or virtual machines based on the EPYC CPU is quite advantageous. One of the main advantages of utilizing EPYC processors is that algorithm developers no longer have to adhere to any certain OS type thanks to this lift-and-shift technique.”

Read more on govindhtech.com

[techsgreat]

Electronic Mail Promoting: Achieve Out To Your Potential Clients With These Easy Recommendations.

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[govindhtech]

Upgrade Now? AMD 8000 Series: The Best Option

AMD 8000 series CPU

AMD Ryzen Embedded

The AMD XDNA architecture-based AMD 8000 series processors are the company’s first embedded AMD processors to integrate conventional CPU and GPU components with NPUs. These processors are designed to be very versatile and adaptable for a wide range of workloads, particularly those related to industrial artificial intelligence. For many industrial AI applications, such as machine vision, robotics, and industrial automation, embedded solution engineers and developers may take use of the processing power and leading characteristics.

AI is now frequently utilised to improve quality control and inspection procedures in machine vision applications. Additionally, AI can assist robots in optimising their routes in real time and adjusting to changing conditions. Intelligent edge devices in industrial automation may carry out sophisticated analysis and decision-making without requiring cloud access thanks to AI processing. This enables autonomous control, predictive maintenance, and real-time monitoring of industrial operations, improving uptime and decreasing operating costs.

AMD 8000 series

AMD Ryzen 8000 series

As the first AMD Embedded devices to include XDNA architecture, the AMD Ryzen Embedded 8000 Series processors redefined performance standards in terms of processing speed, graphics delivery, and I/O connectivity among AMD industrial processing systems.

AI industrial computing efficiency has advanced significantly with AMD 8000 series processors’ performance-per-watt profile, which is enabled for industrial PCs and automation, machine vision, and robotics applications. A variety of thermal design power (TDP) profiles, ranging from 15W to 54W, are offered by the AMD Ryzen Embedded 8000 Series CPUs.

A top maximum performance of 16 trillion operations per second (TOPS) provided by the NPU is boasted by the processors within this range. It is a strong profile appropriate for demanding and varied industrial computing applications since the complete processor performance scales up to 39 TOPS. GPU-driven AI acceleration in CPU designs is being replaced by onboard NPU integration. Comparing NPUs to traditional parallel/matrix GPU coprocessing, better computational agility and lower power consumption are possible due to the focused, efficient acceleration of AI. A software development kit (SDK) that simplifies development and deployment flexibility at reduced costs, together with an open, royalty-free software ecosystem comprising libraries and inferencing models, are used to do this.

EFFICIENT AND INTEGRATED

In order to provide strong CPU performance and integrated AMD Radeon graphics in a BGA (FP7r2) package for effective, efficient industrial systems, AMD 8000 series processors use the next-generation “Zen 4” core architecture and AMD RDNA 3 graphics. At the industrial edge, quick and seamless AI inferencing and decision-making are made possible by AMD embedded solutions’ new onboard XDNA architectural feature.

This method provides specialised AI inferencing at the processor layer to serve use cases for robotics, machine vision, monitoring, and human-machine interfaces (HMI), while optimising processing and design efficiency. Strong AI inferencing is now possible in a roughly same power envelope because to these additional capabilities, which improve upon the performance-per-watt value of prior Ryzen Embedded Series CPUs.

RICH VISUALS AND I/O

AMD’s Ryzen Embedded 8000 Series CPUs provide plenty of I/O flexibility for specialised accelerators and other add-ons, with 20 lanes of on-chip PCIe Gen4. Along with support for error-correcting code (ECC) for dependable and effective memory transfer, AMD Ryzen Embedded 8000 Series Processors also come with the most recent dual-channel memory support (DDR5 up to 5600MT/s). In order to maximise visual processing and multimedia performance, AMD Ryzen Embedded 8000 Series processors provide potent x86 CPU computing with up to 8 “Zen 4” cores (16 threads).

Integrated AMD Radeon-class graphics also include the most recent AMD RDNA 3 technology. A solitary, compact AMD Ryzen Embedded 8000 Series CPU may drive four separate screens at 4K resolution by using hardware encoding and decoding for well-known video codecs like H.265 and AV1. The AMD Ryzen Embedded 8000 Processors contribute to the versatility of display and HMI setups in industrial systems that use graphical interfaces and status displays, even in areas with limited space and heat.

ACHIEVABLE AND OPEN

An excellent choice for industrial system OEMs looking to extend their AI support capabilities and product portfolios across a variety of performance, power, and graphics-optimized alternatives are AMD Ryzen Embedded 8000 Series CPUs due to their performance and power scalability. An extended design lifespan is supported by planned product availability of up to ten years. Easy access to royalty-free libraries and inferencing models via an open AI software ecosystem facilitates quicker development cycles for designers. Support for Microsoft Windows is provided via the software development kit that is offered. With pretrained models that are accessible on HuggingFace, it also supports well-known AI frameworks like PyTorch and TensorFlow.

AMD is working with Advantech, ASRock, and iBASE, among other embedded OEMs, to provide a wide range of cutting-edge platforms that will support AMD Ryzen Embedded 8000 Series CPUs with them. Long-term design lifecycles are further supported by AMD Ryzen Embedded Series CPUs, which have prolonged product availability.

AI opportunities in the embedded industry have expanded with the arrival of the AMD XDNA architecture and its potent AI engines in a few AMD Ryzen Embedded devices, ushering in an exciting new age for these applications.

Read more on Govindhtech.com

[techsgreat]

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[techsgreat]

Good Solutions To Assistance You Do Well At E Mail Advertising... Advice No. 26 Of 136

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