Which Laptop Would You Recommend? Dell, Apple, HP, Sony, Lenovo (IBM)?

Which laptop would you recommend? Dell, Apple, HP, Sony, Lenovo (IBM)?

Which Laptop Would You Recommend? Dell, Apple, HP, Sony, Lenovo (IBM)? 1

The Apple Macbook. I have a mac and love it! Apple has fantastic service and they are well worth it! They are user-friendly, have great applications, and are small and light!

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What OS does IBM Watson run on?

SUSE Linux Enterprise Server 11What OS does IBM Watson run on?

Which Laptop Would You Recommend? Dell, Apple, HP, Sony, Lenovo (IBM)? 2

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Can I use an IBM Thinkpad X30 keyboard to replace the keyboard in my X31?

I do not believe they are compatible, but check out the specs on there web site

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Will IBM provide a work from home option for developer who is joining with experience?

Yup. Ibm provides Work from home option

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Are IBM and Gateway Processors compatible?

Gateway makes processors? IBM has its own processor? All processors most people are using are either made by AMD (if it is Athlon or Turion or Sempron) or Intel (if it is Pentium, Centrino, or Celeron). Anyways, if you do manage to take the little processor chip out, it will work on any other computer considering that the motherboard is new enough. As for your monitor problem, if your processor is compatible with the motherboard, there is no reason why it should affect the monitor. In computers, dont worry about brands. For example, I can run a Sony Viao Pc with a Dell Monitor, a HP printer, a Toshiba Scanner, and Alienware speakers and everything will still work fine :)

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Why does IBM have to pay $1.5B for someone to take the chip division, can't it just lay everyone off and close down the shop?

Because they still need the chips. IBM's semiconductor manufacturing business produces the chips that IBM uses in their high-end server and storage products. The problem with its semiconductor business was not that its design was necessarily inferior to its competition, but it's the fact that the chips were never sufficiently adopted by the market. IBM believes its chips are still superior to other products for their purposes. nHaving said that, IBM alone (there are few other third-parties that use its chips too, but not much) cannot provide the necessary scale for economical production of complex processors. So, lately IBM semiconductor had incurred about $700-800M in pretax losses each year. Furthermore, the new chips that IBM is designing will require 14nm then 10nm nodes from the current 22nm nodes. This increase in chip density will make IBM's subscale production even more non-economical. nSo, shutting down is out of question, but continued technical progress is daunting under current manufacturing scale. Therefore, IBM decided to sell its semiconductor operations to a third party that has the scale to continue to supply IBM with chips of its own design. n$1. 5B cash proceeds to Global Foundries, which will be part of $4.7B write off IBM will take, is just so that Global Foundries will take its loss making division and operate it for next 10 years. From IBM's perspective, they do one time write off of $4. 7B, but then its future pretax income will increase by $700-800M and still get the chips it needs.Why does IBM have to pay $1.5B for someone to take the chip division, can not it just lay everyone off and close down the shop?

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I have an IBM laptop,there is an icon on the laptop that is an arrow pointing up with a 1 in it, what is it?

Probably num lock (to let you use the numeric keypad embedded in the keyboard)

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What is the difference between Tensorflow and IBM SystemML?

Think of Spark as the analytics operating system for any application that taps into huge volumes of streaming data. MLib . provides developers with a rich set of machine learning algorithms. And SystemML enables developers to translate those algorithms so they can easily digest different kinds of data and to run on different kinds of computersSystemML simplifies the development and deployment of ML algorithms by separating algorithm semantics from underlying data representations and runtime execution plans. This gives data scientists the flexibility to create and customize ML algorithms independent of data and cluster characteristics, explained an IBM Research paper on how it uses compressed linear algebra to fit larger datasets into memory. To wit:'SystemML's language is expressive enough to cover a broad class of ML algorithms: descriptive statistics, classification, clustering, regression, matrix factorizations, dimensions reduction, and survival models for training and scoring. Generally, algorithms that can be expressed using vectorized operations are a good fit for SystemML. 'The SystemML cost-based compiler automatically generates hybrid runtime execution plans that are composed of single-node and distributed operations depending on data and cluster characteristics such as data size, data sparsity, cluster size, memory configurations, while exploiting the capabilities of underlying data-parallel frameworks such as MR [MapReduce] or Spark."What is the difference between Tensorflow and IBM SystemML?What is the difference between Tensorflow and IBM SystemML ?

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