MAdianti22

Thanks for sharing your thoughts, Jorge! Such a great insights especially for those currently still working remotely agile.

I worked on several Agile transformation projects when I was in consulting. From what I have seen, collocation was believed to be the most important aspect that enabled the team to achieve its outcome more effectively and efficiently.

Given the remote working model, several companies maintain their agility through several practices such as strong team alignment, rigid prioritization, and the use of virtual team collaboration tools such as Zoom, Slack, Dovetail software, Github, Sketch. It is also interesting to see how empathy, transparency, and engagement also play significant role in maintaining team collaboration. You might want to consider checking this article out to get more details: https://www.bcg.com/en-us/publications/2020/remaining-agile-and-remote-through-covid

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Thanks for sharing your thoughts on this topic, Blake! I focused on Financial Services and Technology industry when I was still in consulting, and I could not agree more that acquisition costs have always been a tricky challenge not only for traditional banks, but also for the digital banks.

From what I've seen, digital banks would typically enjoy their 'honeymoon' phase by attracting new customers with relatively low acquisition costs, until they got some competition from the new entrants. This is also aligned with what IBM highlights in their report on sustainability of digital bank ( https://www.ibm.com/downloads/cas/XGJGOJWA ).

Looks like the moral of the story is, every player should keep innovating and differentiating themselves in the market to attract customers more affordably. Once the offering starts to become more commoditized, they need to 'pay' more to attract the customers.

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Thanks for sharing, Yasu! This is such a very hot topic today.

I am still a big believer that not every tasks in fund management can be completely replaced by AI. Human and AI should work hand-in-hand to achieve the best outcome.

This article ( https://www.ft.com/content/40c618c6-4c0a-11ea-95a0-43d18ec715f5 ) highlights several pitfalls that an investor should watch out for when relying on AI for their investment decisions. Conflicting investment goals and heavy reliance on historical data, that most of the time is not good indicators for the future outcome, are just a few examples why human judgement is still required in the decision-making process.

Lastly, I am also wondering how AI could help analyzing companies with non-traditional business models (e.g., early stage start-ups, crypto, NFT) that has been growing over the past years.

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This is super interesting topic! I really enjoyed reading this.

I see Clubhouse as a VR company creating a digital world. At >$1BN valuation, what they have done that is so incredible is that they have cracked the code on this virtual space we all hang out.

Clubhouse has captured product market fit realizing that video is not necessary to create a space where we can feel connected and hang out. It will be great to see what is next for Clubhouse. One challenge that I started seeing to emerge is how Clubhouse can continue engaging top content creator/influential people while keeping the ecosystem self-sufficient. Unlike, Instagram or Twitter, Clubhouse does not really allow someone else to participate on behalf of those important speakers!

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Such an interesting topic, Zander! Thanks for sharing.

Your thoughts on AI and ML in this aspect are very thought provoking I would love to see what’s next for streaming. Netflix has a huge market opportunity in capturing more space in India and Asia altogether to significantly increase their membership base.

Machine learning is the best solution on the content to capture more users. However, in addition to that, I am wondering how we can use analytics more to help the producers/directors come up with ideas and create new content.

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This is fantastic! Thanks for sharing such a well-crafted post.

This is a revolutionizing way to look at data storage and solve today’s overwhelming crisis. As we have seen this rapid shift into WFH, the need for and storage of data is important now more than ever. AWS, Google, Alibaba spend millions maintaining storage for companies and individuals large and small.

It would also be safekeeping our data in case of a global shock. For example a global cyberattack or a mass internet outage would make our systems useless.

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Thanks for sharing a well-thought of post, Hoon Chung!

I’d like to think there will be a hybrid model in the future. AI is not at a stage where it can fully take over. Human and machine will need to work hand it hand.

We need higher computing power to accelerate the learning of AI to be able to implement it autonomously in society. We need deep learning that could demonstrate a strong ability to help machines with reasoning — a skill that is very important to advance many AI applications to include basic common sense, dealing with challenging situation, and making complex decisions.

Jobs that are at risk to be automated will see a workforce in need of retraining. Companies like Amazon and Walmart have taken steps to address this as a responsible duty to their employees.

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