It's incredibly hard to become a customer of @Telstra so you can give them money. They absolutely despise money, and do everything in their power to erect as many obstacles as possible in the way of a normal person establishing a billing relationship with them.

Lately there have been various rumours in the media about myself and Jumbo in relation to Williams. To clarify things, Jumbo is not and will not invest any money in my career. 1/2

Of course we’re collectively looking at career opportunities, however this is certainly not our philosophy and strategy. I hope to announce my future plans soon, be patient 😉 2/2

'Treasure Gods' - Sangha Nidhi' and 'Padma Nidhi', Tirumala, Tirupati.

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These are the two guards guarding the Wealth and Treasure of Lord Sri Venkateswara.

They are representatives of two treasures of Kubera, the God of Wealth.

One guard who is holding shangam (conch) on both the hands is known as Shanka Nidhi ('nidhi' means wealth).

On the other side, the guard who is holding Lotus flowers on both the hands is known as Padma nidhi.

Shangu is from the ocean which includes all types of wealth like pearls and corals.

Why shagam in his hand? Because shangam only gives the sound of 'omkaram'.

'Padmam' is the symbol of water sources in land like river, lakes, tanks etc. which is very important for all living beings.

As per the tradition, these guards are installed at the third entrance of the temple.

One enters the holy shrine after saluting the first protection threshold - Sankha Nidhi and Padma Nidhi.

X : Our executive team is concerned that we need to up our game in order to out innovate Amazon.
Me : Do you map?
X : Yes
Me : Like this?
X : No. What's that?
Me : A map of a tea shop.

X : Why is that a map?
Me : Long story, all to do with how space has meaning. To keep it short, maps help people to focus on user needs, the components involved, to communicate missing components and scenario play ideas like staff becoming robots.

Me : They’re also good for measuring and managing capital flow, making investment decisions, removing bias and getting rid of duplication.
X : I don’t see how that helps with innovation?

Me : Well, innovation is a tricky word because we use it to describe many things. If you’re talking about differentiation with the adjacent unexplored then you’re experimenting in the “uncharted” space e.g. immortality with magic provided by the special custom built kettle.

X : That sounds like nonsense.
Me : A lot of what people think will be the next great innovation is nonsense. Actually, most of it is. That’s the nature of the uncharted space, it’s experimental, high risk and generally results in failure.
X : We need more reliable innovation.

👇 Thread. New deck getting published this week: "Consumer startups are awesome, and here's what I'm looking to invest in at Andreessen Horowitz." If you want to read it, subscribe to my newsletter here: https://t.co/262t8eh0wf

1/ A lot of new consumer technologies have been introduced to US households in the last 100 years. But it's taken many of them - like the telephone - more than 50 years to get to the majority of the US. Why is that?

2/ We had to literally teach people how to use phone. Which end goes to your mouth, which goes to your ear. Say "hello" when people call. The motivation of consumers to talk to their friends has always been there, but we had to teach the behavior

3/ If you compare phones to the latest technologies, there's been a huge shift. Things are being picked up much faster.

4/ Even while there's been all this innovation recently, physically speaking, we are still the same human beings from 100,000 years ago.

1 There's a chasm between an NLP technology that works well in the research lab and something that works for applications that real people use. This was eye-opening when I started my career, and every time I talk to an NLP engineer at @textio, it continues to strike me even now.

2 Research conditions are theoretical and/or idealized. A huge problem for so-called NLP or AI startups with highly credentialed academic founders is that they bring limited knowledge of what it takes to build real products outside the lab.

3 A product is ultimately a thing that people pay for - not just cool technology or user experience. But I’m not even talking about knowledge gaps in go-to-market work. I'm talking purely technical gaps: how you go from science project to performant + delightful user experience.

4 Most commoditized NLP packages solve well-understood problems in standard ways that sacrifice either precision or performance. In a research lab, this is not usually a hard trade-off; in general, no one is using what you make, so performance is less important than precision.

5 In software, when you’re making something for real people to use, these tradeoffs are a big deal. Especially if you’re asking those people to pay for what you’ve made (can’t get away from that pesky GTM thinking). They expect quality, which includes precision AND performance.