The use of AI in Finance is about to take off. Make sure your infrastructure is ready.


In 2016, financial fraud losses in the UK totalled £768.8m. That's up 2% on 2015, according to Financial Fraud Action UK.


Artificial Intelligence is a powerful tool capable of providing financial organisations with a range of benefits to combat this challenge, including the ability to automate risk analysis, detect and investigate fraud, help with regulatory intelligence and automate IT functions.


As long as you have equally powerful IT technology to drive it.




IBM power
AI in the enterprise: Avoid hitting the infrastructure performance wall.

Given the current - and potential - capabilities of AI, it's not surprising that many businesses want to introduce it into their organisation to increase competitive advantage.


Despite all the opportunities AI can deliver, businesses are realising that this emerging environment can be a formidable undertaking. There is no one-size fits-all solution, businesses are experimenting to find the AI infrastructure that's right for them.


In fact, nearly 23% of businesses are already on their 3rd generation AI infrastructure, according to the IDC report.


AI applications use much greater data and demand powerful processing to carry out all the AI tasks required. Unfortunately, businesses sometimes take on AI without knowing when they will hit the wall with server performance.


So, what do you need to know to make sure your AI infrastructure is fit for purpose?


Watch the video

Hitting the wall with your server infrastructure?




Read the experts' recommendation


Download IDC's report and you will find out:

  • On-premise and cloud infrastructure limitations with AI
  • Most common shifts for AI server infrastructure
  • Your next steps to infrastructure readiness


Overcome AI infrastructure limitations with IBM Power9.



The latest IBM® Power Systems™ servers are designed from the ground up to meet large, complex data challenges like AI, HPC and deep learning.


Perfect for managing mission-critical data and operational data stores and data lakes, as well as delivering the best solution for cognitive computing, IBM® Power Systems™ servers have the additional advantage of industry leading reliability and security.


As a result, many organisations of all sizes trust the partnership of IBM and Logicalis to provide the backbone of their IT infrastructure for commercial, cognitive and database workloads.



With an IBM Power Systems AC922 server you can:


  • Boost I/O throughput by 5.6 times compared to comparable x86 servers1
  • Deploy enterprise-supported solutions for HPC and AI
  • Deliver nearly 4x more performance over competitive x86 alternatives on key AI frameworks such as TensorFlow and Caffe2



Learn more about the capabilities of IBM® Power Systems™ servers.


Read about the IBM Power Advanced Compute AC922 server - the best server for enterprise AI.


Logicalis
IBM Server

Why Logicalis and IBM?


Logicalis is an international provider of integrated IT solutions and managed services, providing expert consultation on communications and collaboration, data centre and cloud solutions, and information and data management.


As an IBM Platinum Partner with over 20 years' experience, Logicalis is best placed to deliver solutions that can leverage the full capability of IBM's market leading solutions.


For a free evaluation of your IT infrastructure please contact our expert team:




1. 5.6x more I/O bandwidth – tested results are based on IBM Internal Measurements running the CUDA H2D Bandwidth Test Hardware: Power AC922; 32 cores (2 x 16c chips), POWER9 with NVLink 2.0; 2.25 GHz, 1024 GB memory, 4xTesla V100 GPU; Ubuntu 16.04. S822LC for HPC; 20 cores (2 x 10c chips), POWER8 with NVLink; 2.86 GHz, 512 GB memory, Tesla P100 GPU Competitive HW: 2x Xeon E5-2640 v4; 20 cores (2 x 10c chips) / 40 threads; Intel Xeon E5-2640 v4; 2.4 GHz; 1024 GB memory, 4xTesla V100 GPU, Ubuntu 16.04

2. Results of 3.8X are based IBM Internal Measurements running 1000 iterations of Enlarged GoogleNet model (mini-batch size=5) on Enlarged Imagenet Dataset (2240x2240). Power AC922; 40 cores (2 x 20c chips), POWER9 with NVLink 2.0; 2.25 GHz, 1024 GB memory, 4xTesla V100 GPU ; Red Hat Enterprise Linux 7.4 for Power Little Endian (POWER9) with CUDA 9.1/ CUDNN 7;. Competitive stack: 2x Xeon E5-2640 v4; 20 cores (2 x 10c chips) / 40 threads; Intel Xeon E5-2640 v4; 2.4 GHz; 1024 GB memory, 4xTesla V100 GPU, Ubuntu 16.04. with CUDA .9.0/ CUDNN 7. Software: IBM Caffe with LMS Source code https://github.com/ibmsoe/caffe/tree/master-lms




The use of AI in Finance is about to take off. Make sure your infrastructure is ready.


In 2016, financial fraud losses in the UK totalled £768.8m. That's up 2% on 2015, according to Financial Fraud Action UK.


Artificial Intelligence is a powerful tool capable of providing financial organisations with a range of benefits to combat this challenge, including the ability to automate risk analysis, detect and investigate fraud, help with regulatory intelligence and automate IT functions.


As long as you have equally powerful IT technology to drive it.


IBM power

AI in the enterprise: Avoid hitting the infrastructure performance wall.

Given the current - and potential - capabilities of AI, it's not surprising that many businesses want to introduce it into their organisation to increase competitive advantage.


Despite all the opportunities AI can deliver, businesses are realising that this emerging environment can be a formidable undertaking. There is no one-size fits-all solution, businesses are experimenting to find the AI infrastructure that's right for them.


In fact, nearly 23% of businesses are already on their 3rd generation AI infrastructure, according to the IDC report.


AI applications use much greater data and demand powerful processing to carry out all the AI tasks required. Unfortunately, businesses sometimes take on AI without knowing when they will hit the wall with server performance.


So, what do you need to know to make sure your AI infrastructure is fit for purpose?


Watch the video

Hitting the wall with your server infrastructure?


Read the experts' recommendation


Download IDC's report and you will find out:

  • On-premise and cloud infrastructure limitations with AI
  • Most common shifts for AI server infrastructure
  • Your next steps to infrastructure readiness

Overcome AI infrastructure limitations with IBM Power9.


The latest IBM® Power Systems™ servers are designed from the ground up to meet large, complex data challenges like AI, HPC and deep learning.


Perfect for managing mission-critical data and operational data stores and data lakes, as well as delivering the best solution for cognitive computing, IBM® Power Systems™ servers have the additional advantage of industry leading reliability and security.


As a result, many organisations of all sizes trust the partnership of IBM and Logicalis to provide the backbone of their IT infrastructure for commercial, cognitive and database workloads.


With an IBM Power Systems AC922 server you can:

  • Boost I/O throughput by 5.6 times compared to comparable x86 servers1
  • Deploy enterprise-supported solutions for HPC and AI
  • Deliver nearly 4x more performance over competitive x86 alternatives on key AI frameworks such as TensorFlow and Caffe2

Learn more about the capabilities of IBM® Power Systems™ servers.


Read about the IBM Power Advanced Compute AC922 server - the best server for enterprise AI.



Logicali
IBM Server

Why Logicalis and IBM?


Logicalis is an international provider of integrated IT solutions and managed services, providing expert consultation on communications and collaboration, data centre and cloud solutions, and information and data management.


As an IBM Platinum Partner with over 20 years' experience, Logicalis is best placed to deliver solutions that can leverage the full capability of IBM's market leading solutions.


For a free evaluation of your IT infrastructure please contact our expert team:



1. 5.6x more I/O bandwidth – tested results are based on IBM Internal Measurements running the CUDA H2D Bandwidth Test Hardware: Power AC922; 32 cores (2 x 16c chips), POWER9 with NVLink 2.0; 2.25 GHz, 1024 GB memory, 4xTesla V100 GPU; Ubuntu 16.04. S822LC for HPC; 20 cores (2 x 10c chips), POWER8 with NVLink; 2.86 GHz, 512 GB memory, Tesla P100 GPU Competitive HW: 2x Xeon E5-2640 v4; 20 cores (2 x 10c chips) / 40 threads; Intel Xeon E5-2640 v4; 2.4 GHz; 1024 GB memory, 4xTesla V100 GPU, Ubuntu 16.04

2. Results of 3.8X are based IBM Internal Measurements running 1000 iterations of Enlarged GoogleNet model (mini-batch size=5) on Enlarged Imagenet Dataset (2240x2240). Power AC922; 40 cores (2 x 20c chips), POWER9 with NVLink 2.0; 2.25 GHz, 1024 GB memory, 4xTesla V100 GPU ; Red Hat Enterprise Linux 7.4 for Power Little Endian (POWER9) with CUDA 9.1/ CUDNN 7;. Competitive stack: 2x Xeon E5-2640 v4; 20 cores (2 x 10c chips) / 40 threads; Intel Xeon E5-2640 v4; 2.4 GHz; 1024 GB memory, 4xTesla V100 GPU, Ubuntu 16.04. with CUDA .9.0/ CUDNN 7. Software: IBM Caffe with LMS Source code https://github.com/ibmsoe/caffe/tree/master-lms