There is a growing divide between those researching Machine Learning Knowledge Center (ML) in the cloud and those trying to perform inferencing using limited resources and power budgets.
Researchers are using the most cost-effective hardware available to them, which happens to be GPUs filled with floating point arithmetic units. But this is an untenable solution for embedded inferencing, where issues such as power are a lot more important. The semiconductor industry is bridging this divide using more tailored hardware structures and mapping technology that can convert between cloud-based learning structures and those that can be deployed in autonomous vehicles, IoT devices and consumer products. https://semiengineering.com/bridging-machine-learnings-divide/
KUALA LUMPUR (Feb 8): The FBM KLCI rose 3.06 points or 0.2% on bargain hunting and after China said January exports and imports increased 11.1% and 36.9% respectively from a year earlier.
Bullish bets on most Asian currencies drop as yields spike lifts dollar: Reuters poll Christina Martin 4 MIN READ
(Reuters) - Investors trimmed their long positions in most emerging Asian currencies in the last two weeks, a Reuters poll showed, as rising Treasury yields helped the dollar rebound from a three-year low touched in late January.
KUALA LUMPUR: The ringgit opened lower against the US dollar today on a lack of interest in the local unit, dealers said.
At 9.00 am, the ringgit stood at 3.9160/9210 against the greenback from Wednesday's close of 3.9070/9100.
A dealer said the US dollar remained bullish against the local currency with positive momentum indicators picking up, and expected to climb higher, but could be temporarily disrupted by a technical pullback before moving up again.
A chip maker, Nvidi, pops after hours, giving some life to a beaten-down market Nvidia exceeded analysts' expectations for income and revenue. The company had a provisional benefit of $133 million because of tax reform. https://www.cnbc.com/2018/02/08/nvidia-earnings-q4-2018.html
Nvidia shares jumped more than 14 percent Thursday after the company reported better-than-expected earnings for the fiscal fourth quarter. After the earnings call ended the stock was more than 9 percent higher than the closing price of $217.52 per share.
SuperPanda Berkshire, what u expect next earnings, >4m? 06/02/2018 10:58
Bro, I think it will be around 4.5m as the global sales of semicon remains strongly. Compre the globally result of Q1 and Q4 in17 , Q4 result is around 1.3times higher than Q1. Just my 2 cents
Beatnodie, yup the needs still remain strongly in Q4 2017. Sometimes mr markets will behave irrationally. For me, as long as the company still perform nicely, I will just hold. I don’t care how the fluctuation is after I bought the shares at bargain price.
Lai It's time to share my opinion To be honest , altho the price go till 1.45 but i didn't even touch it because like i said earlier "it is just the beginning, the fall is happening right now and will go further" My suggestion is hold your bullet and wait i conlanfirm this MMSV can go till 1.30 , lai wait together with me
when market down, must pick correct stock with higher chance to rebound fast. select stock with potential catalyst to boost its price.
the only catalyst for mmsv are next qtr rpt and mainboard transfer. next qtr should not more than 4m (as order was peak at Q2 and Q3) and transfer yet to confirm date.
i compare mmsv and masteel and decided to buy masteel. as per today, it is the correct decision.
for mmsv, i still have faith but have to patient.
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This book is the result of the author's many years of experience and observation throughout his 26 years in the stockbroking industry. It was written for general public to learn to invest based on facts and not on fantasies or hearsay....
tecpower
3,536 posts
Posted by tecpower > 2018-02-08 20:24 | Report Abuse
There is a growing divide between those researching Machine Learning
Knowledge Center
(ML) in the cloud and those trying to perform inferencing using limited resources and power budgets.
Researchers are using the most cost-effective hardware available to them, which happens to be GPUs filled with floating point arithmetic units. But this is an untenable solution for embedded inferencing, where issues such as power are a lot more important. The semiconductor industry is bridging this divide using more tailored hardware structures and mapping technology that can convert between cloud-based learning structures and those that can be deployed in autonomous vehicles, IoT devices and consumer products.
https://semiengineering.com/bridging-machine-learnings-divide/