Narain Jashanmal

AI based photo editing tools like those from Topaz Labs have been around for a while, but I’ve never found them to be good enough to justify disrupting my otherwise Adobe Lightroom based photo editing workflow.

In the past couple of years, Adobe has added native AI based photo enhancement tools to Lightroom, starting with Super Resolution and more recently Raw Details and Denoise. They’ve also steadily improved these tools while also rebuilding Lightroom to work with Apple silicon for optimal performance.

I have an affection for small, powerful digital cameras but there are fewer of these being made as camera manufacturers seek to differentiate from increasingly photography capable smartphones by investing in larger sensors, image stabilization, articulating screens and high quality electronic viewfinders, all of which make cameras physically larger. These investments have yielded great small mirrorless cameras like the Fuji X-E4, Leica CL (discontinued, sadly) and the Canon R50 (what a camera!), but gone are experiments like the Sony RX1 range, and the development much smaller cameras like Canon GX and SX series, the Panasonic ZS, TZ, LX ranges, Nikon A models, Fujifilm XF10/X70 and Leica TL/CL and compacts seems to be done or close to it. The Ricoh GR III is alone as a larger sensor compact actively being sold (the Leica Q2 is a much bigger camera), and the Sony RX100 range with a 1” sensor lives on but future development seems to be focused toward video oriented cameras in this form factor, such as the ZV-1.

So, I turned to my collection of older small cameras which includes the Panasonic LF1 (2013) a 190g compact with a 1/1.7” 12mp sensor, Panasonic GM1 (2013) a 205g ILC (without lens) with a 16mp micro 4/3 sensor, and Ricoh GR Digital II (2007) a 200g compact with a then large-ish 1/1.75” 10mp sensor.

My hunch was that features like Super Resolution and Denoise would breathe life into the images created with these cameras, in particular RAW files shot under challenging conditions or, at the very least, just increase the resolution to enable greater latitude for cropping and larger prints (if that’s your thing).

I was not disappointed.

Denoise, in particular, delivers impressive results that make unusable images not only acceptable but highly usable.

For example, from the Ricoh GR Digital II, which really struggles with the dynamic range and variety of textures in this scene.

Settings: ISO 100 | f/2.4 | 1/200 sec | Spot metered on the center of the image Light: +1.5 exposure, -70 contrast, -50 highlights, +55 shadows, -30 whites, -5 blacks Color: 5,614 temp, +73 tint, +5 vibrance, +5 saturation, -100 pink, -35 purple Effects: +5 texture, +10 clarity, +30 dehaze Detail: 60 sharpening, 70 masking

This raised the shadows while preserving the highlights but even with ISO 100 there’s a ton of detail destroying noise in the shadows.

Below is with Denoise applied set at 60.

Not only is the noise almost gone, Lightroom accomplished this without smearing the details or introducing any other artefacts which has been the problem of previous noise reduction solutions, especially in-camera software. On the contrary, it appears as though detail has been added to the image, which essentially is what AI-based denoise techniques aim to do.

Because the enhanced output is a new DNG raw file, I tried to further optimize the exposure which re-introduced some noise but still yielded a very usable image with plenty of detail.

This is exciting in a number of ways but primarily for me because it extends the life of older cameras, many of which have both technical and ergonomic features that manufacturers have moved away from.

For example, Leica has stopped making APS-C cameras, many of which are really beautiful and lovely to use, AI based editing tools make it possible to get the best possible images from them.

There are other problems with older cameras – autofocus and low resolution screens/viewfinders are notable examples – but there’s a joy and freedom of being able to take a tiny camera like the Panasonic LF1 everywhere, knowing that I’ll be able to have the control it offers as a photographic device without having to sacrifice image quality.

It also makes photography more accessible than ever for people just getting started as they have a huge range of cameras available to them.

Of course, these tools also make it possible to get even more out of the amazing images produced by the latest modern cameras.

#photography #cameras #editing #tools #ai

I orginally posted this here in September 2022, speculating that Apple might announce their VR headset at their fall event, ahead of the holiday shopping season. They didn’t, but the rumor mill is cranking overtime that they will announce it at WWDC in June.

Reposting as nothing much has changed since last fall.

With the fall Apple (iPhone) event almost upon us, time to speculate if there'll be a “One more thing...” moment.

Apple does things their own way and speculation around a pair of Apple AR/VR glasses has been rampant, but it's remained unclear if, when, how and with what type of product they'd enter the market.

Still, it's interesting to consider the current general personal computing context that could lead Apple to such a move.

Everyone has a phone that connects to the internet.

You can do pretty much everything you want to (and things you didn't even know you wanted to) with that phone though, to riff on Gibson's oft quoted maxim, what you can do on your phone isn't evenly distributed, yet.

There's been some playing around with phone form factors from Samsung, Huawei, Microsoft and Xiaomi but...do you own one of these? Does anyone you know?

There are similar experiments with laptops by folks like Asus and Lenovo (Bjarke Ingels uses one!) but...ditto (other than Bjarke, of course).  Most people are just really happy that Apple brought back MagSafe, removed fans and gave us insanely good battery life.

We've got computers for our desks, our laps, our hands, our wrists, our ears, other, uh, parts of our body, our cars (soft of); but...what about for our faces?

For VR, Meta (fka Facebook) has been the leader with the Quest (née Oculus) series, with the current Quest 2 being the most sold VR headset ever, by a sizeable margin. Steam, DPVR and Vive (aka HTC) have participated in the hardware space for a while, with Steam being prominent in VR software. Pico(aka ByteDance, parent company of TikTok), has started to expand outside China, which has led to recent gains in market share (Insider, Counterpoint). Relative to phones, VR hardware remains a small market with unit sales in the double digit millions.

Smart glasses, which incorporate some combination of outward facing cameras, microphones and speakers into glasses, have been around for a while. Snap was early to market with Spectacles, now in their third generation. Spectacles have cameras and microphones, but no speakers, so they can be used to capture photos and video, but not to take calls or listen to audio. Amazon Echo Framesand Aether take a different direction, featuring a microphone and speakers, but no cameras, they enable you to take phone calls give instructions to a voice assistant and listen to audio. Ray-Ban Stories, created in partnership with Meta, combine cameras, microphones and speakers into the only smart glasses that do it all. Sales info is hard to come by, but this article about the sales of Snap Spectacles up to 2021 indicate that – so far – it's a much smaller market than VR, in the high hundreds of thousands, low millions of units overall.

AR glasses, which overlay digital information onto the physical world have been a tough proposition going all the way back to Google Glass, the challenges of which are well documented. Snap have been working on next-gen Spectaclesthat feature AR, but with their recent restructuring it's unclear how much further investment this project will get or even if a consumer version of these will ever come to market. Recently, Nreal, Lenovo and Vive have launched AR glasses that tether, either physically or wirelessly, to a computer or phone – which do the heavy lifting – and are focused on more narrow use-cases around entertainment, wellness and productivity, rather than being self-contained, general purpose computing devices.

It's been even tougher for MR glasses, which don't just overlay digital objects on to the physical world, but enable those digital objects to interact with the physical world. Magic Leap and Microsoft HoloLens are the canonical examples here. Neither have made it to market as viable consumer products.

This landscape raises a bunch of interesting opportunities and questions for Apple. As noted above, there's been plenty of experimentation in the space of face computers, and Meta has carved out a position for themselves to an extent that no one else has. But, is the Quest today's equivalent of Nokia or Blackberry and  Glass the iPhone? Or is Quest more like Sonos and  Glass the original HomePod?

The general speculation is that Apple will do a full-blown, high-end headset, in a more glasses-like form factor that is AR focused or combines AR and VR.

Given Apple's historically conservative approach to new categories, this would seem to go beyond the realm of speculation into that of fantasy. Apple tends to constrain the capabilities of their first-gen hardware, with a focus on getting the form factor and user experience right, while intentionally limiting the features (to the ones people most likely to care about) in order to have a greater success of consumer adoption.

First-gen AirPods are a good example, they didn't have noise-cancellation, came in only one shape and color and lacked tactile volume controls. What they did feature was a competitive price point, seamless pairing, stable connection, good sound and very good battery life. These initial trade-offs, combined with the Beats acquisition, have helped Apple become a market leader in headphones.

Taking cues from their approach to AirPods, it's safer to bet that  Glass will be something more akin to the Nreal Air or Vive Flow than to the next-gen Snap Spectacles, original Magic Leap or forthcoming Meta headset. A companion device, that tethers either to a Mac or iPhone (probably the latter, wirelessly; maybe the former as well, physically, for development) that's focused on entertainment ( TV, Game Center) and wellness ( Fitness+). If that's what it is, it doesn't need necessarily need cameras which lowers both the cost of materials and simplifies the computational overhead. Even without cameras on the headset itself, there is the opportunity to use the iPhone camera (similar to the way the Watch does) and ARKit overlays from there, though addressing latency (if wirelessly tethered) is non-trivial.

Disclaimer: I worked at Meta from 2014 – 2022, in Reality Labs from 2021 – 2022. Whatever I've written here is based on speculation and/or publicly available info.

#technology #hardware #oculus #apple #meta #vr

HARDWARE

• MBP 14 Pro M1
• iPhone 14 Pro
• iPad Pro 11 M2
• iPad Mini 2020
• Apple Studio Display
• Apple Airpods Max
• Apple Airpods Pro

SOFTWARE

• Nova – IDE
• ChatGPT – Text and code generation
• Midjourney – Image generation
• Photo Prompts – Prompt generation
• Perplexity – Answers
• Tiiny – Web hosting
• Caard – Site builder
• Write.as – Blogging
• Sketch – Design
• Google Workspace – Work email, documents, sheets
• Slack – Collaboration
• Linear – Product management
• Help Scout – Customer support
• Snowplow – Event tracking
• Fathom – Web analytics
• Snowflake – Data warehouse
• Metabase – Analytics, reporting, visualization
• Hey – Personal email
• Apple Freeform – Sketching
• Apple Notes – uh, notes

#hardware #software #tools

Source: Benedict Evans Newsletter No. 472

My preferred order for reading books is audio > ebook > paperback > hardback.

(Except for art and photography books, in which the order is hardback > ebook > paperback.)

Reading an audiobook of course means listening to it and debates abound whether we retain information better or worse if one reads a text or listens to it being read (examples here and here).

But, as ChatGPT says, learning styles vary and, like with many things, practice and repetition build optimal habits to get the most out of an experience.

In 2022 I read 45 audiobooks (full list at the bottom of this post).

The number of books isn’t the thing to anchor on here – listening to articles vs reading them will have a similar effect – rather the habit I’ve found most effective to both parse and retain information is reading several books on the same topic in clusters.

This has two benefits:

1. You listen to variations of the same data, research and anecdotes.

2. You hear different points of view on a given topic.

Several distinct topic clusters emerge in the list of books:

1. Financial speculation and the irrational behavior that drives it. This was a timely topic to go deep on, following the crypto and NFT collapse. Spoiler alert: it’s predictable human behavior that causes these endlessly repeated cycles of boom and bust, divorced from the underlying asset class, which in many cases (see: Beanie Babies, NFTs) have no intrinsic value.

2. Inclusive product design. An important and under invested in area.

3. Product management and design at Apple. For a company that has a reputation for secrecy there’s more information available on this topic about Apple than pretty much any other company.

4. Financial (mis)adventures of ultra high net worth individuals and the structures that enable them. An evergreen topic.

5. Frameworks for thinking. Mental models on how to approach problem solving.

The main way I find subsequent books is via references in a current book. In most cases it leads to books that go deeper into a topic, like branching roots, but sometimes it takes you to whole new tree.

This was the case with Strangers to Ourselves, by Rachel Aviv, which was referred to by Tom Vanderbilt in You May Also Like. It’s not a book I would’ve otherwise found my way to but I’m very glad Tom led me to it as it’s a powerful and moving book.

Looking at this list, another thing that stands out is that there’s only one novel (Red Pill by Hari Kunzru, which is excellent).

Novels are almost never read by their authors. Red Pill is and it’s all the better for it. Voiceover actors tend to act out novels, altering their voices for different characters and I find it very distracting. Hari doesn’t do this (or at least I don’t remember him doing it).

While not all non-fiction books are read by their authors, there’s a greater prevalence and the voiceover actors who read non-fiction books either don’t act them out or when they do, do so subtly.

This is one thing that makes Apple’s announcement about AI audiobooks interesting. Will these AI readers act? If so, will it be subtle? What models were used to train the voices? How do they handle non-Western/Anglo-Saxon names and words? Can an author train an AI to read their books so that it sounds like them?

I’m intrigued to try audiobooks read by AI readers and also think this is bridges a valuable gap by potentially creating audiobooks of the many books that previous didn’t have audio editions, which is a very welcome development.

Full list of books in reverse chronological order (links go to Apple Books or Audibooks.com):

1. Strangers to Ourselves by Rachel Aviv

2. You May Also Like by Tom Vanderbilt

3. A Short History of Financial Euphoria by J.K. Galbraith

4. Money Mania by Bob Swarup

5. Irrational Exuberance by Robert J. Shiller

6. The Great Beanie Baby Bubble by Zac Bissonnette

7. Amusing Ourselves to Death by Neil Postman

8. Move Fast and Break Things by Jonathan Taplin

9. Cinema Speculation by Quentin Tarantino

10. When Women Lead by Julia Boorstin

11. Like, Comment, Subscribe by Mark Bergen

12. Status and Culture by W. David Marx

13. The Laws of Simplicity by John Maeda

14. Weapons of Math Destruction by Cathy O’Neil

15. Dark Horse by Todd Rose & Ogi Ogas

16. Technically Wrong by Sara Wachter-Boettcher

17. Mismatch by Kat Holmes

18. Imaginable by Jane McGonigal

19. How Design Makes the World by Scott Berkun

20. The Paradox of Choice by Barry Schwartz

21. The New Breed by Kate Darling

22. Predictably Irrational by Dan Ariely

23. Loved by Martina Lauchengco

24. Change by Design by Tim Brown

25. Sprint by Jake Knapp, John Zeratsky & Braden Kowitz

26. User Story Mapping by Jeff Patton & Peter Economy

27. Start with Why by Simon Sinek

28. After Steve by Tripp Mickle

29. Inspired by Marty Cagan

30. Insanely Simple by Ken Segall

31. Creative Selection by Ken Kocienda

32. Red Pill by Hari Kunzru

33. Build by Tony Fadell

34. Lucifer’s Banker Uncensored by Bradley C. Birkenfeld

35. Butler to the World by Oliver Bullough

36. Moneyland by Oliver Bullough

37. Don’t Believe a Word by David Shariatmadari

38. Reality+ by David J. Chalmers

39. Thinking in Bets by Annie Duke

40. Thinking in Systems by Donella Meadows

41. The Scout Mindset by Julia Galef

42. How to Turn Down a Billion Dollars by Billy Gallagher

43. Four Thousand Weeks by Oliver Burkeman

44. The Precipice by Toby Ord

45. The Alignment Problem by Brian Christian

#reading #amazon #books #apple #ideas #ai

It’s been a while since I built a written collection of my thoughts and ideas.

Now feels like a good time to have a place to do so.

Things I’ll write about include:

1. The impact of technology on society and the individual

2. Product and user experience (UX) design

3. Data informed decision making

4. Culture: Books & Films

5. Shopping

Here’s some past work, which will give you an example of what I think and write about:

1. Medium - What is Ambient Computing? - Best Books on the Impact of Technology on Society

2. Hey World -  Glass Speculation - On Demand Delivery

3. Macfilos - Where does the Camera Industry go from here?

#writing #ideas #me

Here’s a picture of me from 2019 when I still worked at Facebook as the Head of Instagram Shopping Partnerships.

I chose this picture because I still mostly look like that, albeit with even less hair and different glasses but I still have that jacket, which is one of my favorite pieces of clothing.

It was a fun time: I had a great team, worked on something that I enjoyed and was passionate about, and while the travel was a bit exhausting, I split my time between New York, London and the Bay Area.

That tells you a bit about me in 2019. What about before then? And now?

These days I work at MUBI as the VP of Product. I split my time between Dubai, Europe, London and New York. I support teams across product management, UX design, data science, and product operations.

I left Meta – that’s how I think about it, I joined Facebook and I left Meta, they were two very different companies – in mid-2021.

In my almost nine years at Facebook, I worked on a bunch of different things. I started in ad sales working with large retail, ecommerce and mobile app advertisers on what’s called direct response advertising i.e. ads that lead to tangible, finite (online) outcomes, think an ecommerce sale or a mobile app install. During my time in ad sales, I helped launch an ad product originally called Offline Conversions which aimed to do the same for offline outcomes i.e. in-store sales, car test-drives. This formed the bridge which took me from ad sales to ad product, where I continued working on Offline Conversions (now know as Conversions API aka CAPI) and all Facebook’s other direct response ad products, including the launch of ads in Instagram Stories. I also built a data playground to help the company understand the composition of ads revenue at a product level, and a go to market for a predictive model of which ads products would accelerate revenue for the company based on their likelihood to drive the most efficient and effective performance for advertisers.

After my time on ads, I moved to Instagram shopping where I helped launch the capability for people to checkout within Instagram and then moved into a role where I supported go-to-market and growth of sellers on checkout across Instagram and Facebook. In my last role at Meta, I worked at Reality Labs where I supported teams in direct to consumer sales of Quest, Portal and Ray-Ban Stories hardware and did strategy work on the role that VR plays in the shopping journey.

Here’s a talk I gave about Instagram shopping just after we launched checkout.

Prior to Meta, I spent 10 years at my family business, the Jashanmal Group, which was founded by my great-grandfather in 1919 with a single shop in Basra, Iraq. My longest role there was as a General Manager running several different businesses, including print media distribution, travel retail and a chain of bookstores.

Here’s a talk from that time, in which I discuss the role that shopping, as a form of self-actualization, plays in people’s lives:

I studied screenwriting at NYU Tisch, from where I graduated in 2001, and started my career as a filmmaker. I got lucky and by March 2002 was on set in Goa, India directing my first (and to date, only) feature film, Refuge, which played at several film festivals in 2003 but was never distributed commercially.

I was born in Kuwait to an Indian father (who was also born in Kuwait) and a half-German, half-Dutch mother; which makes me a third culture kid. They met at university in Hamburg, Germany, where my father studied Economics and my mother literature.

These are some facts about me, they tell you something about who I am and where I came from and maybe a bit about how I think about things.

#ideas #me