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Apple’s 2021 Mac CPU roadmap reportedly adds 32-core chips

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Apple’s in-house silicon could scale well past the eight-center (or somewhat four-in addition to four-center) M1 you find in passage level Macs. Bloomberg sources guarantee Apple’s 2021 guide is impressively more forceful, to where the organization is purportedly trying chips for better quality work areas (counting a “half-sized” Mac Pro) with upwards of 32 superior centers.

That is not the same number of as in AMD’s 64-center Threadripper, yet it would obscure the 28-center Xeon accessible in the Mac Pro and might convey huge additions for intensely multithreaded errands.

Faster desktops could show up by later 2021, in spite of the fact that the insiders said the Mac Pro is just scheduled to show up “by 2022.”

You may see jumps forward in mid-level frameworks, as well. Mac is supposed to be planning chips for better quality MacBook Pros and iMacs with upwards of 16 superior centers and four high-effectiveness centers.

Quite possibly’s Apple may stay with eight or 12 centers relying upon chip creation capacities, yet you’d consider these to be as ahead of schedule as the spring and proceeding through the fall.

Also, truly, Apple is clearly quick to improve illustrations execution too. The organization is accepted to test 16-and 32-center GPUs for iMacs and better quality MacBook Pros. Its best quality work areas, in the interim, may get 64-and 128-center GPUs that could be “several times” snappier than the AMD designs in current Intel-based models. You’d need to stand by until late 2021 or 2022 to see those most progressive visuals, notwithstanding.

There are numerous unanswered inquiries. How well does Apple’s ARM-based design mean superior PCs? Will there be devoted GPUs, altogether higher RAM limits and (on the Mac Pro) PCIe spaces? Apple’s M1 is frequently quicker than tantamount Intel chips and some of the time beats AMD’s, yet there’s no assurance future CPUs will surpass their x86 reciprocals.

Apple may guarantee an edge in the PC space. As of now, AMD and Intel PC processors top out at eight centers. That will undoubtedly change, however Apple could stir up the business in the event that it conveys 12-or 16-center chips before its opponents.

They could be quicker for multithreaded applications and in any case offer execution you probably won’t expect in current portables. It’s protected to state Apple has high expectations, if these holes are precise — it needs to beat the opposition in certain regards, not simply keep pace.

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Dubai Marks the Global Launch of Dyna.Ai, a Singaporean Startup

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Dyna.Ai announced its worldwide launch at the Dubai Fintech Summit. In order to better serve its wide range of clients—which include traditional banks, digital banks, fintechs, insurance companies, and other businesses—Dyna.Ai has expanded its operations throughout Asia, the Middle East, the Americas, Europe, and Africa.

Dyna.Ai is currently setting up offices in the Kingdom of Saudi Arabia, Nigeria, and the United Arab Emirates in the Middle East and Africa.

Additionally, Dyna.Ai disclosed its applications for a variety of industries. Dyna.AI, a leading AI company, improves critical business operations in the financial and other sectors. Enhancing marketing, customer acquisition, risk management, and operational productivity are all made possible by its solutions.

Dyna.Ai presented its enterprise-level generative AI models with retrieval-augmented generation, sophisticated customization, intensive data curation, and improved performance at its global launch. Two solutions are part of the AI platform: Dyna Avatar is used for digital human interactions, and Dyna Athena is used for text-to-speech, language, and speech processing. For banks, fintech, and other businesses, both solutions provide task-specific, LLM-powered solutions that improve natural language interactions and make conversations more realistic and interesting.

Real-time digital human interactions are made possible by Dyna Avatar, which offers conversational AI-powered dynamic experiences and automated speech recognition. With upcoming updates, Dyna Avatar, which presently supports English, Arabic, Chinese, Japanese, and Thai, is set to expand its language support even further, improving digital life and influencing the direction of intelligent interaction.

“Our goal at Dyna.Ai is straightforward: enhance life, empower work. The global financial services industry is at a turning point where businesses must quickly adjust to the disruption caused by AI that is taking place in front of them. Business leaders want solutions that give them access to cutting-edge technology so they can stay ahead of the competition in this quickly changing ecosystem, according to Mr. Tomas Skoumal, Chairman of Dyna.Ai.

Dedicated to research and development, Dyna.Ai employs more than half of its workforce for this purpose. The company is constantly hiring people throughout the world to support its ambitious growth plans, including specialists in marketing, technology, and customer success.

Additionally, Dyna.Ai demonstrated its powerful system products, such as the Business Core System and Smart Decision Platform, which combine APIs, centralize data storage, and simplify processes. Another cutting-edge solution that promotes omnichannel mobility and complete digitalization is the Digital Banking System, which enables quick user engagement and growth in transaction volume.

“From the Dubai Fintech Summit, we are excited to launch our global expansion.” A distinctive and cutting-edge RaaS (Result as a Service) business model is by Dyna.Ai, which also offers expert AI solutions in the financial sector. According to Mr. Tomas Skoumal, Dyna Ai’s services can help banks, insurance, wealth management, and fintech companies achieve business outcomes. The company also supports pay-for-performance.

The global management team at Dyna Ai is composed of highly qualified professionals with solid core competencies. These important individuals hold advanced degrees in computer science, AI/ML, statistics, and neuroscience and come from prestigious companies like Standard Chartered Bank, Citibank, JP Morgan Chase, FICO, and digital banking. This multicultural team provides successful application solutions for numerous clients by bringing broad experience in financial services, data analysis, artificial intelligence, software engineering, and business consulting.

Dyna.Ai is able to fulfill the local financial service requirements of different countries while combining the world’s most advanced AI technology by offering local services and operational capabilities in multiple regions.

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Alphabet’s Intrinsic Robotics Unit Reveals Internally Developed AI Models

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Today marks the debut of a set of artificial intelligence models developed by engineers at Alphabet Inc.’s Intrinsic unit, which creates technology that makes programming industrial robots easier.

The Automate 2024 robotics event, held this week in Chicago, featured a presentation by executives describing the AI models. Nvidia Corp. and Google DeepMind, the search engine giant’s AI research division, collaborated to develop some of the neural networks, while others were developed independently.

It used to require a lot of custom code to teach industrial robots how to perform tasks like packing goods into boxes. Sometimes the programming required is so complex that it gets in the way of manufacturers’ attempts to automate their factories. In 2021, Alphabet established Intrinsic with the goal of creating software that would simplify the process of programming robots and increase accessibility to the technology.

A robotic arm must first identify the presence of an object and then carry out “3D pose estimation” before it can pick it up. Finding an object’s location and facing direction is the task at hand. With this information, the robotic arm can determine the best angle to pick up the object from in order to reduce the possibility of falls, collisions with other objects, and other related problems.

An object can be identified and its pose estimated in a matter of seconds by the first AI model that Intrinsic described today. The model was pre-trained by Alphabet’s engineers to interact with over 130,000 different types of objects, the company said. Furthermore, the AI is able to adjust to changes in its working environment, like when lightning patterns shift or the camera that a robotic arm tracks objects with is replaced.

Intrinsic CEO Wendy Tan White explained in a blog post that “the model is fast, generalized, and accurate.” “We are working to make this and similar features easier to develop, deploy, and use by adding them to the Intrinsic platform as new capabilities.”

Today at Automate 2024, the Alphabet division presented two AI projects that were conducted in conjunction with Google DeepMind. The goal of both was to maximize the motion of industrial robots.

As per Intrinsic, the initial endeavor yielded an artificial intelligence instrument capable of simplifying “motion planning.” That involves figuring out the best possible series of movements a robot should make in order to finish a task. The artificial intelligence tool is designed for scenarios in which several autonomous machines must operate in tandem and avoid colliding with one another.

The software receives input in the form of measurements, motion patterns, and tasks assigned to the robot. Then, in order to minimize the need for manual coding, it automatically creates motion plans. The AI tool was able to achieve a 25% improvement over traditional motion planning methods in a simulation involving four robots working together on a virtual welding project.

Optimizing scenarios where two robotic hands collaborate on the same task was the focus of Intrinsic’s other joint project with Google DeepMind. The latter group’s researchers used Intrinsic’s technical resources to create AI software that was optimized for these kinds of use cases. Tan White wrote, “One of Google DeepMind’s methods of training a model—based on human input using remote devices—benefits from Intrinsic’s management of high-frequency real-time controls infrastructure, sensor data, and real-world data enablement.”

At the event, Intrinsic also disclosed a partnership with Nvidia centered on robot grasping accuracy. Previously, the software code that dictates a robotic arm’s method of object pickup required customization for every kind of object the arm came into contact with. That required a substantial amount of labor-intensive manual labor.

Using Nvidia’s robot simulation platform, Isaac Sim, Intrinsic built an AI system capable of automating the procedure. It can produce the code needed for a robot to pick up an object without the need for human input. Additionally, the AI is able to modify this code to account for the reality that various robotic arms frequently pick up objects with various kinds of gripping devices.

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Microsoft Prepares a new AI Model to take on OpenAI and Google

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As reported by the Information on Monday, Microsoft is developing an AI language model internally that is big enough to take on rivals like Alphabet’s Google and OpenAI.

As per the report, which cited two Microsoft employees with knowledge of the effort, the newly hired Mustafa Suleyman, the former CEO of AI startup Inflection and co-founder of Google DeepMind, is in charge of the new model, internally called MAI-1.

The model’s precise goal is still unknown and will be based on how well it functions. The report stated that Microsoft might give a sneak peek at the new model at its Build developer conference later this month.

According to the report, MAI-1 will cost more because it will be “far larger” than the earlier, smaller, open-source models that Microsoft had trained beforehand.

Microsoft released Phi-3-mini, a scaled-down artificial intelligence model, last month in an effort to reach a larger customer base with more affordable choices.

The business has poured billions of dollars into OpenAI and integrated the technology of ChatGPT’s creator into its entire productivity software suite, giving it an early advantage in the race for generative AI.

According to the report, Microsoft has been allocating a sizable cluster of servers with Nvidia graphics processing units and a sizable amount of data to enhance the model.

According to the report, MAI-1 is expected to have approximately 500 billion parameters, whereas GPT-4 from OpenAI is said to have one trillion parameters, and Phi-3 mini measures 3.8 billion parameters.

In addition to hiring several Inflection staff members, Microsoft appointed Suleyman as the head of its recently established consumer AI division in March.

According to the report, the new model is not derived from Inflection, though it might use startup training data.

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