🍀The Hardware Lottery🎰 by Sarah Hooker, Google Brain [ACM]
- The very first computer hardware was extremely focused on solving one particular problem - numerical differentiation or polynomial models. In the 1960s IBM invented the concept of Instruction Set and made migration between hardware easier for software developers. Till the 2010s we have been living in the world of general-purpose hardware - CPUs.
- Computer Science Ideas win or lose not because one superior one to another, but because some of them did not have the suitable hardware to be implemented in. Back Propagation Algorithm, the key algorithm that made the deep learning revolution possible, was invented independently in 1963, 1976, 1988 and finally applied to CNN in 1989. However, it was only three decades later that deep neural networks were widely accepted as a promising research direction and the significant result was achieved with GPUs, that could run massive parallel computations.
- Today hardware pendulum is swinging back to domain-specific hardware like it was the CPU invention
- Hardware should not remain a limiting factor for the breakthrough ideas in AI research. Hardware and Software should be codesigned for the SOTA algorithms. Algorithm developers need a deeper understanding of the computer platforms.
🍀The Hardware Lottery🎰 by Sarah Hooker, Google Brain [ACM]
- The very first computer hardware was extremely focused on solving one particular problem - numerical differentiation or polynomial models. In the 1960s IBM invented the concept of Instruction Set and made migration between hardware easier for software developers. Till the 2010s we have been living in the world of general-purpose hardware - CPUs.
- Computer Science Ideas win or lose not because one superior one to another, but because some of them did not have the suitable hardware to be implemented in. Back Propagation Algorithm, the key algorithm that made the deep learning revolution possible, was invented independently in 1963, 1976, 1988 and finally applied to CNN in 1989. However, it was only three decades later that deep neural networks were widely accepted as a promising research direction and the significant result was achieved with GPUs, that could run massive parallel computations.
- Today hardware pendulum is swinging back to domain-specific hardware like it was the CPU invention
- Hardware should not remain a limiting factor for the breakthrough ideas in AI research. Hardware and Software should be codesigned for the SOTA algorithms. Algorithm developers need a deeper understanding of the computer platforms.
Most people buy Bitcoin via exchanges, such as Coinbase. Exchanges allow you to buy, sell and hold cryptocurrency, and setting up an account is similar to opening a brokerage account—you’ll need to verify your identity and provide some kind of funding source, such as a bank account or debit card. Major exchanges include Coinbase, Kraken, and Gemini. You can also buy Bitcoin at a broker like Robinhood. Regardless of where you buy your Bitcoin, you’ll need a digital wallet in which to store it. This might be what’s called a hot wallet or a cold wallet. A hot wallet (also called an online wallet) is stored by an exchange or a provider in the cloud. Providers of online wallets include Exodus, Electrum and Mycelium. A cold wallet (or mobile wallet) is an offline device used to store Bitcoin and is not connected to the Internet. Some mobile wallet options include Trezor and Ledger.
Pinterest (PINS) Stock Sinks As Market Gains
Pinterest (PINS) closed at $71.75 in the latest trading session, marking a -0.18% move from the prior day. This change lagged the S&P 500's daily gain of 0.1%. Meanwhile, the Dow gained 0.9%, and the Nasdaq, a tech-heavy index, lost 0.59%.
Heading into today, shares of the digital pinboard and shopping tool company had lost 17.41% over the past month, lagging the Computer and Technology sector's loss of 5.38% and the S&P 500's gain of 0.71% in that time.
Investors will be hoping for strength from PINS as it approaches its next earnings release. The company is expected to report EPS of $0.07, up 170% from the prior-year quarter. Our most recent consensus estimate is calling for quarterly revenue of $467.87 million, up 72.05% from the year-ago period.
