Humble Genius
Regular
Nothing has changed? Check the sp![]()
Yep, nothing has changed other than the people who shit themselves yesterday and sold their shares (and now wishing they didn't)
Nothing has changed? Check the sp![]()
Better looking day today. Not a bad thing when those sell offs happen. It just means the average intelligence of the SH group has gone up.
Arm's bigger brethren? Founder of Softbank seeks $100bn war chest to build AI chip behemoth to rival Nvidia, Intel — but is it too little, too late?
By Wayne Williams
published 2 days ago
Project Izanagi will focus on artificial general intelligence
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(Image credit: Shutterstock / glen photo)
The founder of Softbank Group has reportedly set his sights on a new venture: a $100 billion AI chip company named Project Izanagi which could one day rival the dominance of AI leaders such as Nvidia, Intel and AMD.
According to Bloomberg, Masayoshi Son says $30 billion of the required funding for Project Izanagi, which will focus on artificial general intelligence (AGI), is expected to come from Softbank, with the remaining $70 billion potentially sourced from Middle Eastern investors. However, the specifics of the funding and execution are still under wraps, and the project may undergo further evolution.
Project Izanagi is envisioned to work in synergy with Arm, a chip design business in which Softbank holds a 90% stake. However, exactly how the two businesses will interact remains a mystery for now.
An impossible dream?
Despite facing various setbacks in his startup investments, Son's fervor for AGI is palpable. He was quoted by Bloomberg as saying, “AGI is what every AI expert is after. But when you ask them about a detailed definition, a number, the timing, how much computing power, how much smarter AGI is than the human intelligence, most of them don’t have an answer. I have my own answer: I am convinced AGI will be real in 10 years.”
The task of building a company to compete successfully against Nvidia is a formidable one. Nvidia boasts a wealth of talented hardware engineers, highly competitive hardware, and a ubiquitous CUDA software stack, which has been evolving for over 16 years.
It makes sense for Son's Project Izanagi's AI processors to employ technologies such as instruction set architecture (ISA) developed by Arm to give it a head start, but the new venture may also choose to look elsewhere. Softbank is one of the companies rumored to be interested in buying cash-strapped UK chip designer Graphcore.
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Arm's bigger brethren? Founder of Softbank seeks $100bn war chest to build AI chip behemoth to rival Nvidia, Intel — but is it too little, too late?
Project Izanagi will focus on artificial general intelligencewww.techradar.com
Nice average. U just need 400 more to get it to a pretty figureCould not help myself, although I didn't get them at 30 cents, I am still happy.
And just for people that think I am full of sh#t, this is what I have brought in
the last month, ( Ok I am in debt ) but just showing because this is how much.
confidence I have in the Company and I am ready to buy more if the opportunity
arises.
As I said before, it is going to make me or break me, only time will tell.
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Afternoon Cassip & Diogenese ,It looks like Jurgen Bruckner is on the ball:
https://www.frankfurter-vermoegen.com/institutionelle-kunden/unsere-fonds
Jürgen Brückner
- ➣ Mainly responsible for DigiTrends since inception
- ➣ Diploma in Economics,
- ➣ Co-founder and Managing Director of Wertefinder VV from 2009 – 2019
- ➣ 25 years of asset management at Deutsche Bank and Dresdner Bank, Managing Director Deutsche Bank, Moscow
- ➣ Management of a japan. Mutual funds (€500 million)
- ➣ Various functions in derivatives and bond trading in Düsseldorf, Frankfurt, Moscow and Madrid
- ➣ Over 10 years as an independent asset manager
https://www.frankfurter-vermoegen.com/institutionelle-kunden/unsere-fonds/digitrends-aktienfonds
DigiTrends is a pure equity fund that focuses primarily on technology, medical technology, environmental technology and renewable energies. High barriers to market entry ensure above-average growth rates and sustainable returns on sales in these business segments. An extremely important success factor is that not only established companies are taken into account, but also those that can be assigned to the so-called "Emerging Growth" values. These companies have an above-average position in the value chain due to their key technologies or competencies and are therefore able to achieve high margins. The products of these companies are indispensable for the production of a wide range of other products and are therefore used in a wide variety of sectors. Examples include augmented reality, the Internet of Things, 5G and wearables. This multiplier effect increases return opportunities while reducing risk within the framework of broad diversification.
https://documents.anevis-solutions.com/fraverm/DigiTrends_Aktienfonds_I.pdf 20240223
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I agree, but maybe they will offer exclusivity, in certain sectors?..In response to point 5 that is questionable and doesn’t go with the idea of leaning forward into Buisnesss. The hidden company that would stop BRN from producing silicone for Gen 2 would need to bring unbeatable value or we are shooting ourselves in the foot so to speak.
"Since there are severe restrictions on heat generation, particularly for embedded devices, both higher performance and lower power consumption are required in AI chips"Renesas Develops New AI Accelerator for Lightweight AI Models and Embedded Processor Technology to Enable Real-Time Processing
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ByBusinesswire
February 26, 2024
Results of Operation Verification Using an Embedded AI-MPU Prototype Announced at ISSCC 2024
Renesas Electronics Corporation, a premier supplier of advanced semiconductor solutions, today announced the development of embedded processor technology that enables higher speeds and lower power consumption in microprocessor units (MPUs) that realize advanced vision AI. The newly developed technologies are as follows: (1) A dynamically reconfigurable processor (DRP)-based AI accelerator that efficiently processes lightweight AI models and (2) Heterogeneous architecture technology that enables real-time processing by cooperatively operating processor IPs, such as the CPU. Renesas produced a prototype of an embedded AI-MPU with these technologies and confirmed its high-speed and low-power-consumption operation. It achieved up to 16 times faster processing (130 TOPS) than before the introduction of these new technologies, and world-class power efficiency (up to 23.9 TOPS/W at 0.8 V supply).
Amid the recent spread of robots into factories, logistics, medical services, and stores, there is a growing need for systems that can autonomously run in real time by detecting surroundings using advanced vision AI. Since there are severe restrictions on heat generation, particularly for embedded devices, both higher performance and lower power consumption are required in AI chips. Renesas developed new technologies to meet these requirements and presented these achievements on February 21, at the International Solid-State Circuits Conference 2024 (ISSCC 2024), held between February 18 and 22, 2024 in San Francisco.
The technologies developed by Renesas are as follows:
(1) An AI accelerator that efficiently processes lightweight AI models
As a typical technology for improving AI processing efficiency, pruning is available to omit calculations that do not significantly affect recognition accuracy. However, it is common that calculations that do not affect recognition accuracy randomly exist in AI models. This causes a difference between the parallelism of hardware processing and the randomness of pruning, which makes processing inefficient.
To solve this issue, Renesas optimized its unique DRP-based AI accelerator (DRP-AI) for pruning. By analyzing how pruning pattern characteristics and a pruning method are related to recognition accuracy in typical image recognition AI models (CNN models), we identified the hardware structure of an AI accelerator that can achieve both high recognition accuracy and an efficient pruning rate, and applied it to the DRP-AI design. In addition, software was developed to reduce the weight of AI models optimized for this DRP-AI. This software converts the random pruning model configuration into highly efficient parallel computing, resulting in higher-speed AI processing. In particular, Renesas’ highly flexible pruning support technology (flexible N:M pruning technology), which can dynamically change the number of cycles in response to changes in the local pruning rate in AI models, allows for fine control of the pruning rate according to the power consumption, operating speed, and recognition accuracy required by users.
This technology reduces the number of AI model processing cycles to as little as one-sixteenth of pruning incompatible models and consumes less than one-eighth of the power.
(2) Heterogeneous architecture technology that enables real-time processing for robot control
Robot applications require advanced vision AI processing for recognition of the surrounding environment. Meanwhile, robot motion judgment and control require detailed condition programming in response to changes in the surrounding environment, so CPU-based software processing is more suitable than AI-based processing. The challenge has been that CPUs with current embedded processors are not fully capable of controlling robots in real time. That is why Renesas introduced a dynamically reconfigurable processor (DRP), which handles complex processing, in addition to the CPU and AI accelerator (DRP-AI). This led to the development of heterogeneous architecture technology that enables higher speeds and lower power consumption in AI-MPUs by distributing and parallelizing processes appropriately.
A DRP runs an application while dynamically changing the circuit connection configuration between the arithmetic units inside the chip for each operation clock according to the processing details. Since only the necessary arithmetic circuits operate even for complex processing, lower power consumption and higher speeds are possible. For example, SLAM (Simultaneously Localization and Mapping), one of the typical robot applications, is a complex configuration that requires multiple programming processes for robot position recognition in parallel with environment recognition by vision AI processing. Renesas demonstrated operating this SLAM through instantaneous program switching with the DRP and parallel operation of the AI accelerator and CPU, resulting in about 17 times faster operation speeds and about 12 times higher operating power efficiency than the embedded CPU alone.
Operation Verification
Renesas created a prototype of a test chip with these technologies and confirmed that it achieved the world-class, highest power efficiency of 23.9 TOPS per watt at a normal power voltage of 0.8 V for the AI accelerator and operating power efficiency of 10 TOPS per watt for major AI models. It also proved that AI processing is possible without a fan or heat sink.
Utilizing these results helps solve heat generation due to increased power consumption, which has been one of the challenges associated with the implementation of AI chips in a variety of embedded devices such as service robots and automated guided vehicles. Significantly reducing heat generation will contribute to the spread of automation into various industries, such as the robotics and smart technology markets. These technologies will be applied to Renesas’ RZ/V series—MPUs for vision AI applications.
You have 5 minutes!Chart wise she looks ready for liftoff.
Esq.
Description
Announcing The KnowU™, Know Labs' Wearable Non-Invasive CGM
Announcing the KnowU™, Know Labs' wearable non-invasive continuous glucose monitor (CGM). The KnowU incorporates the sensor the Company plans to submit to the FDA for clearance. This proprietary radio-frequency (RF) dielectric sensor has been tested and proven stable and accurate in a lab setting and is now miniaturized and wearable. The KnowU can be worn with an adhesive, allowing the user to clip the sensor on and off or on the wrist or forearm with a strap. The device, which is significantly smaller and lighter than the prototype, includes on-board computing power and built-in machine learning capabilities. The KnowU is designed to optimize the customer experience – expected to last for years, eliminate costly disposables, have a rechargeable battery, and connect with an easy-to-use companion mobile app.
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Know Labs, Inc. on LinkedIn: Announcing The KnowU™, Know Labs' Wearable Non-Invasive CGM | 13 comments
Today, we announce the KnowU™, our non-invasive wearable continuous glucose monitor that incorporates the sensor we plan to submit to the FDA for… | 13 comments on LinkedInwww.linkedin.com
Chart wise she looks ready for liftoff.
Esq.
Probably go the opposite direction now you’ve opened you mouth lolChart wise she looks ready for liftoff.
Esq.
I was thinking the same.. what has changed that necessitated a more polite approach?The following is a link to a presentation containing a Brainchip created Competitive Analysis Chart at page 13.
You will note beyond Intel and IBM that Google Coral and Deep Learning Accelerators from Nvidia and others are listed and compared to AKIDA which ticks all the boxes.
Today we are told the competitors names are not included basically for politeness sake.
Until today Brainchip has seen no reason to be so polite about Google, Nvidia & others when listing competitors failings compared to AKIDA technology.
What has changed???
My opinion only DYOR
Fact Finder
I don't think you know what a dead cat bounce is, otherwise you wouldn't be putting a rocket ship after itLooks like a dead cat bouncehopefully a close in the 40s to close the gap at .44
Hey Esqui old friend.Chart wise she looks ready for liftoff.
Esq.