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5 of the top small-cap ASX stocks for February
Small-cap stocks can have greater growth potential due to their smaller size. Here is a list of five of the top small-cap ASX stocks for traders.
Rise from the ashes
Regular
Link to register and save your spot for the webinar
us06web.zoom.us
Be there or be square or just hope @TechGirl records it
Welcome! You are invited to join a webinar: Benchmarking AI Inference at the Edge: Measuring Performance and Efficiency for Real-World Deployments.. After registering, you will receive a confirmation email about joining the webinar.
Join BrainChip and Edge Impulse in this live video to discover FOMO, the next-generation AI object-detection tool that leverages BrainChip’s neuromorphic architecture. We'll also guide participants through benchmarking activities, demonstrate the availability of BrainChip’s model library, and...
Stable Genius
Regular
I hope Know Labs have their patents sorted re their glucose monitor as Apple is making the same product.
Jon Fingas
February 23, 2023, 6:31 am
Apple's long-running quest to bring blood glucose monitoring to the Apple Watch appears to be moving forward. Bloombergsources claim the company's no-prick monitoring is now at a "proof-of-concept stage" and good enough that it could come to market once it's smaller. The technology, which uses lasers to gauge glucose concentration under the skin, was previously tabletop sized but has reportedly advanced to the point where an iPhone-sized wearable prototype is in the works.
The system would not only help people with diabetes monitor their conditions, but would ideally alert people who are prediabetic, the insiders say. They could then make changes that prevent Type 2 (adult onset) diabetes.
Apple declined to comment. The project has supposedly been in development for a long time. It began in 2010, when an ailing Steve Jobs had his company buy blood glucose monitoring startup RareLight. Apple is said to have kept the effort secret by operating it as a seemingly isolated firm, Avolonte Health, but folded it into a previously unknown Exploratory Design Group (XDG). CEO Tim Cook, Apple Watch hardware lead Eugene Kim and other top leaders have been involved.
Any real-world product is likely years away, according to Bloomberg. The industry also doesn't have a great track record of bringing no-prick monitors to market. In 2018, Alphabet's health subsidiary Verily scrapped plans for a smart contact lens that would have tracked glucose using tears. Even major brands with vast resources aren't guaranteed success, in other words, and it's not clear how accurate Apple's solution would be.
There are strong incentives to bring this tech to wearables. The Apple Watch is frequently marketed as a health device and can spot signs of atrial fibrillation, low blood oxygen levels and (as of Series 8) ovulation cycles. Non-intrusive glucose monitoring could make it an indispensable tool for those with diabetes — you wouldn't need a dedicated device that invades your skin, such as a continuous glucose sensor that sends info from an electrode-equipped thin needle to an external receiver. That painless approach could give the Apple Watch an edge over competing smartwatches.
Apple is reportedly closer to bringing no-prick glucose monitoring to the Watch
Jon Fingas
February 23, 2023, 6:31 am
Apple's long-running quest to bring blood glucose monitoring to the Apple Watch appears to be moving forward. Bloombergsources claim the company's no-prick monitoring is now at a "proof-of-concept stage" and good enough that it could come to market once it's smaller. The technology, which uses lasers to gauge glucose concentration under the skin, was previously tabletop sized but has reportedly advanced to the point where an iPhone-sized wearable prototype is in the works.
The system would not only help people with diabetes monitor their conditions, but would ideally alert people who are prediabetic, the insiders say. They could then make changes that prevent Type 2 (adult onset) diabetes.
Apple declined to comment. The project has supposedly been in development for a long time. It began in 2010, when an ailing Steve Jobs had his company buy blood glucose monitoring startup RareLight. Apple is said to have kept the effort secret by operating it as a seemingly isolated firm, Avolonte Health, but folded it into a previously unknown Exploratory Design Group (XDG). CEO Tim Cook, Apple Watch hardware lead Eugene Kim and other top leaders have been involved.
Any real-world product is likely years away, according to Bloomberg. The industry also doesn't have a great track record of bringing no-prick monitors to market. In 2018, Alphabet's health subsidiary Verily scrapped plans for a smart contact lens that would have tracked glucose using tears. Even major brands with vast resources aren't guaranteed success, in other words, and it's not clear how accurate Apple's solution would be.
There are strong incentives to bring this tech to wearables. The Apple Watch is frequently marketed as a health device and can spot signs of atrial fibrillation, low blood oxygen levels and (as of Series 8) ovulation cycles. Non-intrusive glucose monitoring could make it an indispensable tool for those with diabetes — you wouldn't need a dedicated device that invades your skin, such as a continuous glucose sensor that sends info from an electrode-equipped thin needle to an external receiver. That painless approach could give the Apple Watch an edge over competing smartwatches.
Deadpool
Did someone say KFC
Yeah good that we got a mention, but the way they word it allures to an innuendo of untruth.5 of the top small-cap ASX stocks for February
Small-cap stocks can have greater growth potential due to their smaller size. Here is a list of five of the top small-cap ASX stocks for traders.www.ig.com
Not claims we friggin are.
Brainchip Holdings is an artificial intelligence company that claims to be the world's first commercial producer of neuromorphic processors that can mimic the way the human brain processes sensory inputs.
Rise from the ashes
Regular
I've purchased this for my Dad after that last episode he had. These sensors stop working after 14 daysI hope Know Labs have their patents sorted re their glucose monitor as Apple is making the same product.
Apple is reportedly closer to bringing no-prick glucose monitoring to the Watch
Jon Fingas
February 23, 2023, 6:31 am
Apple's long-running quest to bring blood glucose monitoring to the Apple Watch appears to be moving forward. Bloombergsources claim the company's no-prick monitoring is now at a "proof-of-concept stage" and good enough that it could come to market once it's smaller. The technology, which uses lasers to gauge glucose concentration under the skin, was previously tabletop sized but has reportedly advanced to the point where an iPhone-sized wearable prototype is in the works.
The system would not only help people with diabetes monitor their conditions, but would ideally alert people who are prediabetic, the insiders say. They could then make changes that prevent Type 2 (adult onset) diabetes.
Apple declined to comment. The project has supposedly been in development for a long time. It began in 2010, when an ailing Steve Jobs had his company buy blood glucose monitoring startup RareLight. Apple is said to have kept the effort secret by operating it as a seemingly isolated firm, Avolonte Health, but folded it into a previously unknown Exploratory Design Group (XDG). CEO Tim Cook, Apple Watch hardware lead Eugene Kim and other top leaders have been involved.
Any real-world product is likely years away, according to Bloomberg. The industry also doesn't have a great track record of bringing no-prick monitors to market. In 2018, Alphabet's health subsidiary Verily scrapped plans for a smart contact lens that would have tracked glucose using tears. Even major brands with vast resources aren't guaranteed success, in other words, and it's not clear how accurate Apple's solution would be.
There are strong incentives to bring this tech to wearables. The Apple Watch is frequently marketed as a health device and can spot signs of atrial fibrillation, low blood oxygen levels and (as of Series 8) ovulation cycles. Non-intrusive glucose monitoring could make it an indispensable tool for those with diabetes — you wouldn't need a dedicated device that invades your skin, such as a continuous glucose sensor that sends info from an electrode-equipped thin needle to an external receiver. That painless approach could give the Apple Watch an edge over competing smartwatches.
Cost isn't an issue since I'd do anything for him no matter the cost. Type 2 so not subsidised.
Glucose Monitoring Readers & Sensors | FreeStyle Libre AU
Our glucose monitoring systems can test your glucose levels without finger pricking, a useful diabetes device for detecting glucose trends & tracking patterns.
www.freestylelibre.com.au
jtardif999
Regular
There were no separate announcements made with the revenue earned in the first half of the year, why would there necessarily be any announcements made if there had been more licence money in the second half of the year? The licence arrangement BrainChip have with Megachips as a sales partner makes it possible for third parties to licence Akida through Megachips and BrainChip doesn’t have to announce those deals to the market. So we will continue to see this kind of thing I think and we will have to rely on the financials as we have done here to see the progress. AIMO.
NASA Recruits Microchip, SiFive, and RISC-V to Develop 12-Core Processor SoC for Autonomous Space Missions
NASA’s JPL (Jet Propulsion Lab) has selected Microchip to design and manufacture the multi-core High Performance Spaceflight Computer (HPSC) microprocessor SoC based on eight RISC-V X280 cores from…
www.eejournal.com
Rise from the ashes
Regular
Hmmm…could this be us?
Businesses can embed Palantir Edge AI on sensors and cameras in manufacturing plants — as well as on machines in processing factories — to increase efficiency and improve quality control. When these sensors examine components as part of a production line, models deployed with Palantir Edge AI identify defective products and separate them for inspection or repair.
Palantir Edge AI deploys at the tactical edge in low-bandwidth or disconnected environments to support cameras and other sensors scanning across wide areas. Computer vision models deployed with Palantir AI Inference Platform search for key objects — such as vehicles, people, or ships. When an entity of interest is found, the camera and platform move along with it. Palantir Edge AI generates metadata-only streams to reduce bandwidth while still providing actionable insights. For example, it can run on cameras on ships — without a network connection — to accurately detect and classify boats on the horizon as friendly or threatening, feeding back into an on-board alerting system.
Organizations seeking to manage their energy consumption and reduce production costs can deploy Palantir Edge AI on sensors, allowing AI models to analyze power utilization across systems. Models can then initiate actions to reduce system activity and improve efficiency.
www.palantir.com
AI-driven Decision-making
Palantir Edge AI is Palantir’s AI orchestration and sensor fusion engine that runs on disconnected, remote endpoints.
It enables autonomous decision-making for on-hardware models consuming real-time sensor, radio, acoustic, geo-registration, and time series data. The platform operates in low-bandwidth, low-power conditions, bringing AI to all of your IoT devices — from drones to wind turbines to manufacturing robots.Businesses can embed Palantir Edge AI on sensors and cameras in manufacturing plants — as well as on machines in processing factories — to increase efficiency and improve quality control. When these sensors examine components as part of a production line, models deployed with Palantir Edge AI identify defective products and separate them for inspection or repair.
Palantir Edge AI deploys at the tactical edge in low-bandwidth or disconnected environments to support cameras and other sensors scanning across wide areas. Computer vision models deployed with Palantir AI Inference Platform search for key objects — such as vehicles, people, or ships. When an entity of interest is found, the camera and platform move along with it. Palantir Edge AI generates metadata-only streams to reduce bandwidth while still providing actionable insights. For example, it can run on cameras on ships — without a network connection — to accurately detect and classify boats on the horizon as friendly or threatening, feeding back into an on-board alerting system.
Organizations seeking to manage their energy consumption and reduce production costs can deploy Palantir Edge AI on sensors, allowing AI models to analyze power utilization across systems. Models can then initiate actions to reduce system activity and improve efficiency.
AI-driven Decision-making
Palantir Edge AI is Palantir’s AI orchestration and sensor fusion engine that runs on disconnected, remote endpoints.
It enables autonomous decision-making for on-hardware models consuming real-time sensor, radio, acoustic, geo-registration, and time series data. The platform operates in low-bandwidth, low-power conditions, bringing AI to all of your IoT devices — from drones to wind turbines to manufacturing robots.
Offerings | Edge AI
Meet Palantir Edge AI. Featuring micro models. Sensor fusion. Continuous deliver. Autonomous decision-making. Anywhere deployment.
VictorG
Member
Interesting but I couldn't find reference to neuromorphic or neural processing.Hmmm…could this be us?
AI-driven Decision-making
Palantir Edge AI is Palantir’s AI orchestration and sensor fusion engine that runs on disconnected, remote endpoints.
It enables autonomous decision-making for on-hardware models consuming real-time sensor, radio, acoustic, geo-registration, and time series data. The platform operates in low-bandwidth, low-power conditions, bringing AI to all of your IoT devices — from drones to wind turbines to manufacturing robots.
Businesses can embed Palantir Edge AI on sensors and cameras in manufacturing plants — as well as on machines in processing factories — to increase efficiency and improve quality control. When these sensors examine components as part of a production line, models deployed with Palantir Edge AI identify defective products and separate them for inspection or repair.
Palantir Edge AI deploys at the tactical edge in low-bandwidth or disconnected environments to support cameras and other sensors scanning across wide areas. Computer vision models deployed with Palantir AI Inference Platform search for key objects — such as vehicles, people, or ships. When an entity of interest is found, the camera and platform move along with it. Palantir Edge AI generates metadata-only streams to reduce bandwidth while still providing actionable insights. For example, it can run on cameras on ships — without a network connection — to accurately detect and classify boats on the horizon as friendly or threatening, feeding back into an on-board alerting system.
Organizations seeking to manage their energy consumption and reduce production costs can deploy Palantir Edge AI on sensors, allowing AI models to analyze power utilization across systems. Models can then initiate actions to reduce system activity and improve efficiency.
AI-driven Decision-making
Palantir Edge AI is Palantir’s AI orchestration and sensor fusion engine that runs on disconnected, remote endpoints.
It enables autonomous decision-making for on-hardware models consuming real-time sensor, radio, acoustic, geo-registration, and time series data. The platform operates in low-bandwidth, low-power conditions, bringing AI to all of your IoT devices — from drones to wind turbines to manufacturing robots.
Offerings | Edge AI
Meet Palantir Edge AI. Featuring micro models. Sensor fusion. Continuous deliver. Autonomous decision-making. Anywhere deployment.
I'd be keen to know what their power saving claims are and if they can perform one or few shot learning.
Rise from the ashes
Regular
NASA’s Psyche Mission Continues Preparation for Launch in 2023
After a one-year delay to complete critical testing, the Psyche project is targeting an October 2023 launch.
Techinvestor17
Regular
Oh my god how nice it is again to read this forum, job well done cleaning up. Can someone explain to me how the upcoming report could be a huge? Any revenue would have been disclosed in the 4C in January no? Or will this report cover sales/revenue from January, or is it what developments might be reported by management that could potentially be price sensitive? Nevertheless I am loosing sleep due to excitement
We have a CNN to SNN conversation module so can’t rule us out on that premise alone
Rise from the ashes
Regular
Might be something worth keeping an eye on.NASA’s Psyche Mission Continues Preparation for Launch in 2023
After a one-year delay to complete critical testing, the Psyche project is targeting an October 2023 launch.www.jpl.nasa.gov
Linda Herridge – Kennedy Space Center
Mentions neuromorphic processor.
No direct mention of neuromorphic or neural processing…. But found this white paper
A Generational Shift in AI
Palantir Edge AI
Technical Whitepaper — 2022
Interesting….
Many of the most valuable possible actions — whether in combat or in manufacturing — are time dependent. Shuttling data back to the cloud for processing and analysis means a high-priority target may have changed location — or an operational failure may have occurred. The compet- itive advantage will accrue to those organizations who can make decisions on edge devices in seconds and in potentially disconnected environments.
…autonomous decision-making across edge devices and environments. Designed for situations where time and efficiency matter, it operates in low-bandwidth, low-power conditions — including on drones, aircraft, ships, robots, buildings, and satellites.
Extremely lightweight and power-efficient to deploy, Palantir Edge AI minimizes the data that needs to be stored and transmitted — enabling low-latency, real-time decision-making at the device level if necessary. It runs on cloud infrastructure, on-premise GPU servers, or Size, Weight, and Power (SWaP) optimized hardware.
Critically, users can hot swap models in real time without breaking the flow of sensor data through the system. This also means that if a model crashes, it does not impact downstream users who rely on that sensor output.
The architecture is implemented through utilizing standard, open-protocol interfaces that facilitate communication between Palantir Edge AI and processors. The solution handles a variety of sensor input formats, such as RTSP/RTP, NITF, GeoTIFF, and MPEG-TS. Finally, it supports outputs in open standard formats — such as Parquet, CoT, MISB 0601/0903 KLV, MPEG-TS, and GeoJSON — which enables data and insights to be sent downstream to other subsystems with little to no integration work required.
Palantir Edge AI supports multi-sensor models for customers who need to fuse data across diverse payloads. For example, if a customer uses RF and EO collection, they can field AI models with Palantir, combining both modalities to achieve higher fidelity detections of entities of interest (e.g., military equipment).
These fusion models can be deployed to Palantir Edge AI and run on edge devices, such as spacecraft. Additionally, separate Palantir Edge AI instances can communicate with each other on a mesh network, enabling sensor fusion and teaming across edge equipment.
So which former leading chip maker needs an AI accelerator for their CPU?
Okay appears to be software company and solutions.
Still interesting considering what they are claiming to achieve. Here is a video I found with the CEO. Unable to watch atm as need to go somewhere but will later, nonetheless thought I’d post for anyone still interested.
Still interesting considering what they are claiming to achieve. Here is a video I found with the CEO. Unable to watch atm as need to go somewhere but will later, nonetheless thought I’d post for anyone still interested.
Palantir AI Inference Platform | Enabling AI at the Edge, with Palantir CEO Alex Karp
equanimous
Norse clairvoyant shapeshifter goddess
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