- The rise of robotics creating a new operating environment as remote working and monitoring has become more prominent in the pandemic
How AI and machine learning tools will help to prepare for a post COVID-19 new normal – increasing faster detection, prevention, response and recovery for the future
- Humans train machines to perform tasks and machines amplify human insight and intuition. The collaboration of both enables business to achieve the largest boosts in performance. What are the common challenges and breakthroughs?
- Humans and machines are not adversaries but partners. Working side by side, they can unleash new level of productivity, enhance internal operations and completely transform our economy. How do businesses reimagine the relationship between workers and machines?
- Case studies and best practise
- Utilising cloud infrastructure but keeping assets at the edge of the network which decreases the likelihood of bandwidth issues
The growing need of compatibility and connections between cellular technology and networks with edge infrastructure to back up networks
Having infrastructure close to the cloud, which will minimize errors with data processing and save time
Alerts and analytics within the plant floor will run at a faster pace as it is close to the originating source of data and the network
Using IoT Analytics at the edge can capture sensor data from factory equipment improve production and yield
- Blockchain and AI as catalysts to improve business processes and drive competitive advantage by making projects more efficient at a faster pace
IoT technologies such as digital twin and AR/VR, fundamentally shifting industry dynamics and pushing decision-making to a new level
AI systems are learning from us. Properly trained bots with a global view and localised perspective will greatly enhance user experiences and business IQ.
- Training requires different sets of roles and jobs. How do we train AI to mimic human behaviors?
- How do we train AI systems beyond the fundamentals, i.e. empathy, gestures or a world view?
Businesses are using AI to identify potentially malicious software behaviours and contain any emerging cyberthreats faster and easier than ever before.
- ML and AI make it easier to respond to cybersecurity risks
- Collaborative efforts between intelligent machines and cybersecurity experts
- Forming valuable partnerships across the ecosystem and leveraging the right cutting edge platforms to drive change for a better future within your business
Exploring the convergence of emerging technologies and the wider impact it has on digital transformation, working with and benefiting one another
- Overcoming barriers to work out if the inference is at the cloud or at the edge as AI becomes more infused in applications as it is being processed within the device (must be at the cloud first)
- How intelligent connectivity is being enabled by AI
- Testing the robustness of AI-enabled edge applications and how they gain insight into the performance of connectivity (ie. Between a vehicle and an application hosted within the network)
- Businesses need a talent strategy to scale up AI projects and ensure AI success. What is the shortfall in AI talent and manpower? How do businesses upskill the current workforce and make the transition to a new era of human and machine collaboration?
- Talent strategies for different industry sectors, from bank & finance, logistics & supply chain, healthcare
- Attract international high-skilled talents and grow global talent network
- What are the key challenges of adopting AI and ML in investment banking? Compared to the traditional valuation methods, what are the benefits of using ML models?
- How do ML solutions address the transparency and trust issues? What are the steps taken to ensure users understand and trust the results of automated valuation?
- What are the lessons learned by using AutoML to build, create and deploy ML models?
Driving up the value of AI relies on building a collaborative ecosystem internally and externally.
- Innovate together with AI start-ups to maintain competitive advantages
- Support AI start-ups to build and grow businesses with technical and financial resources, as well as business know-how
- Digital transformation creates IT complexity. AIOps enables IT to function at the spend that modern businesses need.
- AIOps bridges automation, service management and performance management
- Adapt to AIOps technologies and strategies
Covid-19 is pushing on digital banking and the Union Bank of the Philippines is accelerating its digital transformation.
- Data infrastructure and governance
- ML and data analytics to predict and understand consumer behaviours
AI applications
Building on devices that communicate, generate and analyse data in real-time, reducing the long-distance transfer of data between connected devices and cloud servers
Decreasing the dependency on latency and bandwidth of the network
Data management at the edge – analysing and filtering data at the edge to reduce cloud processing, cloud storage and costs overall
- People want to data to go to the cloud but there is a risk of the security aspect as it uses virtual technology to host applications off site, vs. on prem
Developing security business models and ensuring that the cloud system using strong data security features
Prioritizing encrypting sensitive information and data as cloud applications often integrate with other services and databases
In the last few months corporates have been forced to face the recurring themes of frantic adoption rate of new digital technologies, having a strong foundation for SMAC (Social, Mobile, Analytics and Cloud) to incorporate the latest tech trends, or a digitally skilled workforce that can provide customised services or products to the constant changing realities. Whilst the term ‘5G’ has been a buzz word for half a decade now and has long been forecasted to be revolutionary; plenty of other technologies such as AI is directly impacting business strategy and operations.
This session will discuss what other technologies enterprises should be focusing on the developments of advancements in analytics through automation, distributed cloud system - bridging the gap between data storage and computation, data-driven policing?
Success for broadcasters, linear channels and pay TV operators depends on delivering the right combination of linear and on-demand services, blending hybrid TV with OTT. Understand the future potential with up-to-date market analysis, hear the stories of successful transformation projects, and find out how to develop hybrid TV services.
[Keynote] Transforming Broadcast Platforms, Operations and Technology | Broadcasters and pay TV platforms must transform to survive new digital competitors, meet the growing expectations of consumers and stay profitable. Revealing the priorities for investment – from a compelling front-end user experience to efficient back-end infrastructure able to deliver content, metadata and search across TV and OTT.
[Case Study] Launching a Modern Satellite TV Platform | Going inside a TV platform operation in the Philippines that enables content owners to launch new channels rapidly, reaching an audience of 4.5 million viewers while enhancing the bouquets of DTH operators.
[Fireside Chat] How Linear Broadcast Will Evolve in the OTT/Hybrid World | Charting strategies for established broadcasters to thrive in the modern media market – from analogue to digital, from broadcasting to multiplatform, VOD and OTT, from mobile services to new advertising initiatives.
Picking the optimum business model from SVOD to AVOD, and creating the right blend of content, tech and user experience tailored to each market are essential for a successful modern media business. Going it alone or partnering with others, competing with the global streaming giants or targeting a niche, hear how successful direct-to-consumer platforms have flourished.
[Keynote] Competing With the Global Giants – a Recipe for OTT Success in Asia | In an OTT market dominated by Silicon Valley behemoths, the pressure is on for regional players to compete. The secret is in understanding local content tastes and business models while delivering world-beating levels of user experience.
[Case Study] Building Scalability and Elasticity Into OTT Services | How OTT services can scale up for peak traffic without building excess capacity: inside the architecture needed to deliver brilliant user experience and quality-of-service to millions of viewers without busting the budget.
[Keynote] Engineering an OTT Platform at Scale | Behind the scenes of one of the biggest new OTT platform launches to see the engineering and technology architecture needed to deliver consistent performance and a great user experience.
[Fireside Chat] Competing in the OTT Business: Using Data to Get the Business Model Right | Optimizing OTT business models is challenging: From securing the best talent and content rights, to tuning the mix of revenue between advertising, subscriptions and content sales, to managing the balance between owned-and-operated platforms and social media. Explore how data science and machine learning can be the solution.
The growth of consumer platforms is driving a content renaissance underpinned by new ways to make that content more efficiently and securely. Explore case studies using the latest creative production tech, from collaboration in the cloud to remote editing, and debate whether building, buying or partnering is the best way to develop new tools.
[Keynote] Combining OTT and Free to Air Broadcast | An amazing case study involving the Taiwan National Opera House and how broadcasters enabled viewers to select their preferred choice of camera angle and coverage.
[Panel] On the Screen and on the Field: What Broadcasters and Esports Producers Can Learn From Each Other | What can esports learn from traditional sports broadcasters about reaching a mass audience? And what can broadcasters learn about innovative formats and production techniques? A panel of both groups come together to debate.
[Panel] Build, Buy or Partner? | A closing panel of technology leaders debates the right model for investing in technology for content production and distribution. Should it be developed in house, bought from suppliers, or rented in the cloud? What's the role of open source, and does the future lie in collaboration and shared technology?
Tech take-aways and advancements from Release 16
Achieving continuous connectivity with wireless and wireline convergence
Key learnings and take-aways from 5G vertical experimentations, trials and pilots
- How does 5G fit in the 4th industrial revolution’s agenda?
- Reviewing the economics of rolling out 5G
- Establishing an ecosystem of 5G partners and innovators to push the technology roll-out and adoption forward
- The role of governments and regulators in promoting telco innovation
Achieving the four pillars of next-gen network performance
How to get the most of your network: compatibility, scalability, security and performance
The ingenious ways operators are customizing their networks to the needs of new industry vertical customer
Exploring the specialized applications being tested in 5G
From theory to reality: which applications and industry are taking off in the real world?
Key learnings and take-aways from enterprise proof of concepts
How private networks are driving a revolution in connectivity for enterprises
What mix of technology are operators adopting to deploy private networks?
How do operators master managed connectivity for enterprises?
Is 5G the catalyst in realising the adoption and revenue potential of IoT?
Understanding the IoT based 5G services which will drive 5G adoption?
Identifying and overcoming security challenges in 5G IoT
Delivering value beyond connectivity
Achieving the connectivity outcomes enterprises crave with 5G
Crystallising the revenue opportunities and business models
Should operators develop solutions across markets or specialise in just one?
What are the go-to-market strategies you need for industry verticals?
What shifts in tech and thinking do operators need to capture new markets?
OpenStack and Generic VNFM, ETSI-NFV and containers
Developing and ecosystem with partners and vendors
Overcoming challenges and managing costs to deliver transformative OpenStack capabilities
Key steps on the road to cloud-native
Deploying, managing and securing your network with the power of the cloud
The always-on reliable network extended across virtual and hybrid cloud environments
The role of the ultra 5G packet core in SA and non-standalone
Exploring the network functions in the new 5G Core
How does the 5G packet core enable new use cases?
Which killer app will lead to large scale edge deployment?
Using intelligent edge software to roll out new experiential 5G services
Scanning the market to identify the applications with the most promise
Defining the edge and what it means for telcos and enterprises
Insights into how operators are deploying the edge across their networks
Mapping out the edge ecosystem: the role of hyper-scalers, telcos and operators
Requirements of Edge Computing and its applications
Developing an Innovative Edge Computing Solution
POC Experience Sharing
- Overcoming barriers to work out if the inference is at the cloud or at the edge as AI becomes more infused in applications as it is being processed within the device (must be at the cloud first)
- How intelligent connectivity is being enabled by AI
- Testing the robustness of AI-enabled edge applications and how they gain insight into the performance of connectivity (ie. Between a vehicle and an application hosted within the network)
- Blockchain and AI as catalysts to improve business processes and drive competitive advantage by making projects more efficient at a faster pace
IoT technologies such as digital twin and AR/VR, fundamentally shifting industry dynamics and pushing decision-making to a new level
- Forming valuable partnerships across the ecosystem and leveraging the right cutting edge platforms to drive change for a better future within your business
Exploring the convergence of emerging technologies and the wider impact it has on digital transformation, working with and benefiting one another
- The rise of robotics creating a new operating environment as remote working and monitoring has become more prominent in the pandemic
How AI and machine learning tools will help to prepare for a post COVID-19 new normal – increasing faster detection, prevention, response and recovery for the future
- Humans train machines to perform tasks and machines amplify human insight and intuition. The collaboration of both enables business to achieve the largest boosts in performance. What are the common challenges and breakthroughs?
- Humans and machines are not adversaries but partners. Working side by side, they can unleash new level of productivity, enhance internal operations and completely transform our economy. How do businesses reimagine the relationship between workers and machines?
- Case studies and best practise
Driving up the value of AI relies on building a collaborative ecosystem internally and externally.
- Innovate together with AI start-ups to maintain competitive advantages
- Support AI start-ups to build and grow businesses with technical and financial resources, as well as business know-how
AI systems are learning from us. Properly trained bots with a global view and localised perspective will greatly enhance user experiences and business IQ.
- Training requires different sets of roles and jobs. How do we train AI to mimic human behaviors?
- How do we train AI systems beyond the fundamentals, i.e. empathy, gestures or a world view?
- What are the key challenges of adopting AI and ML in investment banking? Compared to the traditional valuation methods, what are the benefits of using ML models?
- How do ML solutions address the transparency and trust issues? What are the steps taken to ensure users understand and trust the results of automated valuation?
- What are the lessons learned by using AutoML to build, create and deploy ML models?
- Businesses need a talent strategy to scale up AI projects and ensure AI success. What is the shortfall in AI talent and manpower? How do businesses upskill the current workforce and make the transition to a new era of human and machine collaboration?
- Talent strategies for different industry sectors, from bank & finance, logistics & supply chain, healthcare
- Attract international high-skilled talents and grow global talent network
Businesses are using AI to identify potentially malicious software behaviours and contain any emerging cyberthreats faster and easier than ever before.
- ML and AI make it easier to respond to cybersecurity risks
- Collaborative efforts between intelligent machines and cybersecurity experts
Covid-19 is pushing on digital banking and the Union Bank of the Philippines is accelerating its digital transformation.
- Data infrastructure and governance
- ML and data analytics to predict and understand consumer behaviours
AI applications
- Digital transformation creates IT complexity. AIOps enables IT to function at the spend that modern businesses need.
- AIOps bridges automation, service management and performance management
- Adapt to AIOps technologies and strategies
- How 5G is facilitating high scale IoT deployments and can assist with the needs of bandwidth and latency requirements
- IoT platforms and technologies tapping into the power of 5G, transforming the enterprise
- Utilising cloud infrastructure but keeping assets at the edge of the network which decreases the likelihood of bandwidth issues
The growing need of compatibility and connections between cellular technology and networks with edge infrastructure to back up networks
Having infrastructure close to the cloud, which will minimize errors with data processing and save time
- Edge Computing for V2V communication – facilitating the exchange of information and predicting danger or errors within the vehicle
- Cloud based solutions and platforms that connect vehicles to mobility services for productivity, telematics and navigation
- 5G connectivity within the vehicle to obtain strong connectivity
- How delivering the right solutions will decrease the risks of compromise your network security
- NBIoT, LPWAN, LoRA evolving networks – weighing the best options
- People want to data to go to the cloud but there is a risk of the security aspect as it uses virtual technology to host applications off site, vs. on prem
Developing security business models and ensuring that the cloud system using strong data security features
Prioritizing encrypting sensitive information and data as cloud applications often integrate with other services and databases
Alerts and analytics within the plant floor will run at a faster pace as it is close to the originating source of data and the network
Using IoT Analytics at the edge can capture sensor data from factory equipment improve production and yield
- Interoperating platforms at a large-scale deployment to reach cost effectiveness of specific solutions
- What are the standards for connectivity and data systems? Who owns the data?
- Building trust at a scale across the ecosystem and overcoming issues of fragmentation
Building on devices that communicate, generate and analyse data in real-time, reducing the long-distance transfer of data between connected devices and cloud servers
Decreasing the dependency on latency and bandwidth of the network
Data management at the edge – analysing and filtering data at the edge to reduce cloud processing, cloud storage and costs overall
As part of a closed door discussion, we are bringing together a select group of APAC’s senior corporate leaders and innovators to delve into what it means to lead an organisation purposefully in 2020. We’ll explore the common challenges leaders have encountered this year and crucially, we’ll share the novel solutions our community is identifying to weather the storm and thrive in uncertain times.
We’re gathering an inspiring group of Founders to talk about fundraising strategies during Covid-19. We’ll be talking about successful approaches to investor outreach and exploring how founders are framing company narrative and pivoting product development to meet their goals in uncertain times.
Be part of our group of change-makers. We’re delving into the tangible actions the tech community needs to take now to attract and retain more women in the industry and in turn help to develop tech products and services that appeal to a diverse range of businesses and individuals.
Beyond career development, how do women in tech achieve career mastery? We’re leaning on the wisdom and guidance of our network of established founders and c-suite leaders who are taking part in this exclusive session to help develop the next generation of women leaders and entrepreneurs.