Work how you like, where you like with Webex

Work how you like, where you like with Webex

Work how you like, where you like with Webex

Work will never be the same. When the pandemic hit, organisations moved almost completely to remote work to keep business running and keep people safe. As many parts of the world emerge from the pandemic, it’s clear that the future of work will be “hybrid” – a mixed mode in which some people work in the office, others from home, and others from anywhere. Hybrid work is about adapting to how teams work best and creating experiences that reach everyone.

Cisco Webex powers a new way of collaborating that’s centred around the work you do, not where you do it—whether it’s in the office, at home, or anywhere in between.


expect to be in the office 10 days or less each month.


believe future meetings will include remote participants.


want changes to make the office safer before they return.

The Future of work is hybrid

Hybrid work is here to stay, and the best hybrid work solutions enable a better way of work that is flexible, inclusive, supportive, secure and managed. Webex is focused an enabling the best experiences for hybrid work. Webex transforms familiar tools and familiar spaces into something more collaborative.

Impressively secure. Incredibly collaborative.

The world becomes your workplace when all of your work is all in one app.


Make and receive calls with colleagues or customers with a fully integrated, carrier-grade cloud phone system.


Drive more inclusive discussions with innovative features that minimise interruptions and amplify every voice.


Create inclusive experiences

Include everyone with features that make sure anyone can participate regardless of their geography, communication style, or language.

Translate in real time

Don’t let language get in the way of how your teams collaborate. Translate real-time into 100+ languages and get post-meeting transcriptions.

Choose your focus

Create a meeting view that works best for you with custom layouts that let you choose the content and people you want to see.

Find your flow with Webex.

Experience hybrid work that can adapt to any industry model and all of your needs

All about next-gen AI: neuromorphic computing

All about next-gen AI: neuromorphic computing

Roughly seventy years ago, Alan Touring asked: “Can machines think?” Given the state of artificial intelligence (AI) today, we still cannot answer that question with absolute certainty. However, collective efforts in this field have produced many artificial hardware and software structures that resemble the human brain and perform computation in a similar way.

Among the many human brain-inspired AI architectures, neural networks and more recently deep neural networks, have the most significant results. Equipped with deep learning algorithms, computers are capable of detecting fraud, autonomously driving cars, serving as virtual assistants, managing customer relations, modelling financial investments and recognising what people are saying and how they look.

Deep neural networks are composed of artificial neurons modelled after biological neurons present in our brains. These neural networks are capable of discovering and learning from complex relations present in the training data. Given the large amount of data collected using IoT devices, advanced sensor networks, and mobile devices, deep neural networks are capable of learning almost anything that humans can.

“Deep neural networks are capable of learning almost anything that humans can.”

Nevertheless, current computation technology is limiting the large-scale application of deep neural networks. These limitations come mainly from current computation technology. Firstly, due to the economics of Moore’s Law, very few companies can fabricate silicon technologies beyond 7 nm. Secondly, current memory technologies are incapable of dealing with very large data loads that grow even faster than Moore’s Law. And finally, the increased computation power requirements have increased cooling energy demands. The overall efficiency of the computation technology is too low to sustain a large, deep neural network load.

To solve the problems of the current computing technology, research institutions and enterprises around the world are making a huge push towards the integration of nanoelectronics into computing hardware in a more innovative way. The common goal is to integrate different ways of processing information that go far beyond Von Neumann’s architecture.

“Neuromorphic chips have an ideal architecture that can support the large-scale adoption of deep neural networks and further the progress of AI.”

One of the most promising novel computation technology efforts is neuromorphic computing; next-generation computation hardware that architecturally resembles the computing structure of a human brain. Namely, neuromorphic processors are designed to have central processing and memory units together to remove the key bottleneck of Von Neumann’s architecture of requiring data exchange mechanisms between these two elements. Designed in this way, neuromorphic chips have an ideal architecture that can support the large-scale adoption of deep neural networks and further the progress of AI.

Neuromorphic computing advantages

The key limiting factor of the current computation technologies is the need to continuously move data between CPU and memory, and this is not what our brains normally do. These limitations impact both the bandwidth and our ability to efficiently train neural network models.

In a typical data analysis scenario today, we are taking human brain-inspired machine learning models and we are imposing them on a processor with Von Neumann architecture, which is very different from how our brains work. This feels out of place and poses the question, can we create a computer chip that operates similarly to our brain?

Another key limiting factor of the Von Neumann architecture is energy efficiency. Today’s computers are extremely power-hungry. According to the study published in Nature magazine, if the data and communication trends continue to increase at the current rate, by 2040 binary operations will consume over 1027 Joules of energy, which exceeds the global energy production of today.

“By mimicking the workings of the human brain, the technology intends to be as energy-efficient.”

Neuromorphic computing is an interdisciplinary field that involves material science, physics, chemistry, computer science, electronics, and system design. The concept attempts to resolve the current limitations of the Von Neumann architecture and intends to create hardware structures that resemble the human brain. Neuromorphic computing technology collocates memory and processing units. By doing so, latency and bandwidth limitations induced by moving large amounts of data between the two can be eliminated. Additionally, by mimicking the workings of the human brain, the technology intends to be as energy-efficient.

The neuromorphic approach has the potential to revolutionise computing as a whole, but its most effective application will be deep neural networks. These networks have a highly parallel model structure that requires specific distributed memory access patterns. The distributed parallelism is difficult to map efficiently onto Von Neumann architecture-based computing hardware.

Exploring the early-use cases

Hewlett Packard Enterprise is at the forefront of research and development into this tech. Government research hubs are also delving into it, including the European Union with its Human Brain Project.

Last year, the neuromorphic chip market was valued at almost $US2 billion and is expected to increase to $11.29 billion by 2027. According to Gartner, there’s a lot of interest there, considering traditional computing tech that uses legacy semiconductors will hit a digital wall in 2025. For now, though, neuromorphic chips aren’t being produced at the commercial scale of CPUs and GPUs. A hold up is that many neuromorphic processors need more advances in emerging technologies such as ReRAM or MRAM. You can find out more about those here.

“Those insights ensure businesses who work with HP will get access to the latest and most efficient storage technology solutions.”

So, there’s still a way to go before real-world applications of neuromorphic semiconductor design become commonplace. The big win comes from keeping compute and memory units together. That means the system doesn’t have to constantly move data around, says John Paul Strachan, who heads the emerging accelerators’ team in the AI Lab at Hewlett Packard Enterprise. Research into AI for enterprise, including brain-based architectures, has been carried out for several years at Hewlett Packard’s labs. Those insights ensure businesses who work with HP will get access to the latest and most efficient storage technology solutions.

How can HPE work for you?

HPE is focused at the forefront of emerging technologies and is constantly incorporating advanced tech into their next-generation products and solutions. A market leader in innovation, how are you taking advantage of HPE solutions? Contact us to find out how HPE products can help your business gain a competitive advantage and put you on the fast-track to achieving your goals.

What employers can do to encourage stellar team performance

What employers can do to encourage stellar team performance

Everyone from venture capitalists to Michael Jordan has praised the value of a synced, talented team. LinkedIn co-founder Reid Hoffman captured the sentiment perfectly when he said, “No matter how brilliant your mind or strategy, if you’re playing a solo game, you’ll always lose out to a team.”

A high-performing team can have big returns, too. According to McKinsey research, “there is a 1.9 times increased likelihood of having above-median financial performance when the top team is working together toward a common vision.”

There is a 1.9 times increased likelihood of having above-median financial performance when the top team is working together toward a common vision.

ou know when your team is performing at the top of their game when the goal-focused group can do things like communicate and collaborate effectively, navigate conflict in real-time and use their complementary skill sets to continually innovate.

And because where and how we work is changing fast – thanks in large to advances in digital technology – the topic of teams has become increasingly relevant. With remote and hybrid work environments emerging as the norm and more freelancers supporting the workforce, leaders have to be extra intentional about nurturing strong, functional teams.

This primer on boosting team performance offers actionable ways to do just that.

Have a purpose + set ambitious goals

For your team to be as impactful as possible, they need to work as a unified force in pursuit of a common goal.

But it’s not all about the end game. Having clear milestones identified over the course of the project ensures your team stays on track and accountable to the rest of the group. By committing fully to one another as much as the project, challenges are mitigated while the chances of success skyrocket.

To be fully aligned, each member of the team has to understand their individual and collective role while trusting that everyone will own and execute their portion of the project. Make that project purpose-driven too and there’s no limit to what can be achieved.

A team is only as strong as its equipment

Regardless of whether your team operates remotely or in person, they’re going to need digital tools and updated devices to accomplish their work.

The right IT solutions will depend on the specifics of your project, but there are a few universal tools your team will inevitably need to maximise its productivity.

In general, focus on digital solutions that support your team in:

  • Mind mapping and brainstorming
  • Analysing data
  • Automating where possible
  • Managing all aspects of the project
  • Utilising a variety of apps
  • Sharing documents and files
  • Staying secure and cybersafe


Collaboration tools are key

As you’re picking your equipment and assessing potential programmes, be sure to spend some extra time evaluating possible collaboration tools.

Invest in hardware and software that make virtual meetings and real-time communication as easy and accessible as possible.

With the rise of remote and hybrid work, collaboration is more important than ever. From here out, there’s no guarantee your team is going to be in the same place at the same time. Invest in hardware and software that make virtual meetings and real-time communication as easy and accessible as possible.

Diversify your team and focus on talent

A diverse team is a strong team. Bringing together individuals with differing educational and/or cultural backgrounds is the best way to add a breadth of skills to your team.

The key is to build teams of appropriate size with complementary talents and attitudes.

Size wise, that’s usually somewhere between seven and 10 people. McKinsey cites research that suggests, “the team’s effectiveness starts to diminish if there are more than ten people on it.” Too big and sub-groups start to form, eroding the team’s cohesion. Too small and you run the risk of slowing the team’s progress.

Top teams also uplift under-performers or help them transition to a different role within the project that better utilises their inherent talents. Doing so typically has a positive impact on morale – and ultimately the group’s performance.

Pair it all with a little mutual respect and individual accountability, and you have yourself a high-performing team.