Weekend Readings: Dec 12,2021

  • Apple’s Long Journey to the M1 Pro Chip. Apple’s M1 Pro/Max is the second step in a major change in computing. What might be seen as an evolution from iPhone/ARM is really part of an Apple story that began in 1991 with PowerPC. And what a story of innovation. (learningbyshipping)
  • Is this how your brain works? Machine learning has incredible promise. I believe that in the coming decades we will produce machines that have the kind of broad, flexible “general intelligence” that would enable them to help us address truly complex, multifaceted challenges like improving medicine through a more advanced understanding of how proteins fold. Nothing we call AI today has anything like that kind of intelligence. (GatesNotes).
  • In a First, Physicists Glimpse a Quantum Ghost. A wave function is not something one can hold in their hand or put under a microscope. And confusingly, some of its properties simply seem not to be real. In fact, mathematicians would openly label them as imaginary: so-called imaginary numbers—which arise from seemingly nonsensical feats such as taking the square roots of negative integers—are an important ingredient of a wave function’s well-proved power to forecast the results of real-world experiments. In short, if a wave function can be said to “exist” at all, it does so at the hazy crossroads between metaphysical mathematics and physical reality. (Scientific American).
  • Addressing the structural foundations of homelessness in the Bay Area. The severity of the Bay Area’s homelessness crisis is visible everywhere—from the tents that crowd under freeways to the increasing number of people sleeping on sidewalks and in doorways. Largely hidden from view, however, are the 457,000 extremely low-income (ELI) households in the region who are making ends meet on an average of $18,000 a year. Over half of ELI households are precariously housed, meaning that they don’t receive any housing assistance and pay more than 30 percent of their income for housing. These households—which include seniors living on fixed incomes, single parents juggling work and child care responsibilities, and essential workers making poverty wages—are at significant risk of housing insecurity and homelessness. (Berkeley blog).
  • The futuristic plan to fix America’s power grid. One of the most important fixes would be physically “hardening” the grid, which means replacing old infrastructure that’s vulnerable to extreme weather with stronger, more resilient upgrades. These are the kinds of solutions you might notice if they pop up in your neighborhood, perhaps in the form of swapping out wooden electric poles for wind-resistant steel or concrete ones, moving power lines underground, or lifting ground-level transformers out of the path of potential floods.  (Recode)

Mid-week Readings. Dec 8, 2021

  • Everyone Is Talking About Data Science. Here’s How J.P. Morgan Is Putting It Into Practice. Paul Quinsee, J.P. Morgan Asset Management’s global head of equities, thought he knew the skills that turned analysts into stars. Like the talent scouts in Money Ball, Michael Lewis’s bestselling book on how data science changed baseball, Quinsee had been watching fundamental research analysts play their game — albeit in less dusty fields — for almost four decades. (Institutional Investor).
  • The Dark Side of 15-Minute Grocery Delivery. Over the last year, cities across the U.S. and Europe have seen a rapid rise in the number of dark stores — mini-warehouses stocked with groceries to be delivered in 15 minutes or less. Operated by well-funded startups such as GetirGopuffJokr and Gorillas, dark stores are quietly devouring retail spaces, transforming them into minimally staffed distribution centers closed to the public. In New York City, where seven of these services are currently competing for market share (including new entrant DoorDash), these companies have occupied dozens of storefronts since July, with expansion plans calling for hundreds more in that city alone. (Bloomberg)
  • Can Apple Take Down the World’s Most Notorious Spyware Company? If Apple were to win this case, it would deal a strong blow against malicious spyware operators, state-sponsored hacking, and the global oppression of democracy activists. However, if defendants were to somehow prevail, it could send a signal that we have entered a new age in which technological pirates are free to run amok without fear of judicial intervention (Slate)
  • Why you should care about Facebook’s big push into the metaverse. Many critics and skeptics have mocked Zuckerberg’s plan to change Facebook from a social media company to a metaverse company. Some critics say that by focusing on the metaverse and renaming itself while the company is reeling from a PR crisis, Facebook is distracting from the problems it creates or contributes to in the real world: issues like harming teens’ mental health, facilitating the spread of disinformation, and fueling political polarization. (Vox)

Weekend Readings – Nov 21, 2021

  • Microsoft and Metaverse: It’s certainly the question of the season: what is the Metaverse? Here is the punchline: the Metaverse already exists, it just happens to be called the Internet.  For well over a year a huge portion of people’s lives was primarily digital. The primary way to connect with friends and family was via video calls or social networking; the primary means of entertainment was streaming or gaming; for white collar workers their jobs were online as well. This certainly wasn’t ideal: the first thing people want to do as the world opens up is see their friends and family in person, go to a movie or see a football game as a collective, or take a trip. Work, though, has been a bit slower to come back: even if the office is open, many meetings are still online given that some of the team may be working remote — for many companies, permanently.(Stratechery)
  • Even though electric and self-driving cars have yet to saturate the market, dozens of companies are at various stages of launching flying cars in a variety of models. Although the earlier prototypes were not successful, they have paved the way for today’s more advanced models. With the more recent development and popularity of drones, several companies have designed passenger models. These include two Chinese companies, XPeng, which is backed by the e-commerce company Alibaba, and EHang, which is supplying the United Arab Emirates with autonomous taxis. The drones run on electric motors. (Quillette)
  • On the wings of Ada Lovelace.She detailed her ideas for a “flying machine” in the spring of 1828, writing to her mother: “I have got a scheme … which, if ever I effect it … is to make a thing in the form of a horse with a steam engine in the inside so contrived as to move an immense pair of wings, fixed on the outside of the horse, in such a manner as to carry it up into the air while a person sits on its back” (April 7, 1828, excerpted in Ada, the Enchantress of Numbers). (UC Berkeley Blog)
  • How well can an AI mimic human ethics? For a long time, a background assumption in many parts of the AI field was that to build intelligence, researchers would have to explicitly build in reasoning capacity and conceptual frameworks the AI could use to think about the world. Early AI language generators, for example, were hand-programmed with principles of syntax they could use to generate sentences. Now, it’s less obvious that researchers will have to build in reasoning to get reasoning out. It might be that an extremely straightforward approach like training AIs to predict what a person on Mechanical Turk would say in response to a prompt could get you quite powerful systems. (Vox)
  • What Is Customer Satisfaction Score (CSAT)? A CSAT score is easy to calculate. It’s the sum of all positive responses, divided by the total responses collected, then multiplied by 100. The outcome leaves you with the overall percentage of satisfied customers at your business. A big strength of Customer Satisfaction Score lies in its simplicity: It’s an easy way to close the loop on a customer interaction and determine whether or not it was effective in producing happiness. (Hubspot)

Early Week Readings – Nov 15,2021

  • Apple’s Relentless Strategy, Execution, and Point of View. Apple’s announcement of “Apple Silicon” is important for many reasons. Delivering on such an undertaking is the result of remarkable product engineering.(Learning By Shipping)
  • Qualcomm is researching machine learning at the edge. So far, ML at the edge has only involved inference, the process of running incoming data against an existing model to see if it matches. Training the algorithm still takes place in the cloud. But Qualcomm has been researching ways to make the training of ML algorithms at the edge less energy-intensive, which means it could happen at the edge. (StacyOnIoT)
  • Wi-Fi HaLow is now certified and ready for action. About five and half years ago the Wi-Fi Alliance announced that it was planning a new Wi-Fi standard just for the IoT. It was dubbed Wi-Fi HaLow and the IEEE standard was called 802.11ah. The whole goal of the new standard was to tackle the high power consumption of traditional Wi-Fi and to have the signals stretch over longer ranges.(StacyOnIot)
  • Tableau Pledges to Train 10 Million Data People. With demand for data skills outpacing supply, data skills are no longer exclusively essential for data scientists or technical roles — to build truly data-driven organizations, employees across the entire enterprise must be data literate. This will help companies become data-driven and strengthen the Tableau Economy – a rapidly growing ecosystem of businesses, tech partners and people leading the world’s data transformations. (Tableau Blog)
  • Why We Forgive Humans More Readily Than Machines. Today, much of that moralizing is not aimed at the wrong pair of socks but at AI and at those who create it. Often the outrage is justified. AI has been involved in wrongful arrestsbiased recidivism scores, and multiple scandals involving misclassified photos or gender-stereotypical translations. And for the most part, the AI community has listened. Today, AI researchers are well aware of these problems and are actively working to fix them. (Scientific American)
  • A Half Century Later, the Journey of Apollo 8 Still Inspires. It’s hard to believe Apollo 8’s voyage around the moon had originally been scheduled as a less audacious Earth-orbit mission to test the whole moonship “flotilla”: the monstrous, still problem-prone Saturn 5 booster, along with the recently redesigned, and only once-flown-by-astronauts Apollo command ship, which was fashioned to carry a three-person crew to and from Earth and into moon orbit. For a landing, it was to fly in tandem with a lunar lander that would ferry two astronauts to and from the moon’s surface. (Scientific American)

Weekend Readings

  • The Metaverse: What It Is, Where to Find it, and Who Will Build It. Technology frequently produces surprises that nobody predicts. The most common conceptions of the Metaverse stem from science fiction. Here, the Metaverse is typically portrayed as a sort of digital “jacked-in” internet – a manifestation of actual reality, but one based in a virtual (often theme park-like) world, such those portrayed in Ready Player One and The Matrix. And while these sorts of experiences are likely to be an aspect of the Metaverse, this conception is limited in the same way movies like Tron portrayed the Internet as a literal digital “information superhighway” of bits. (Matthewball.vc)
  • GE and the Belief in Management Magic. The breakup of an American colossus reveals an essential corporate truth: No stratgy can erase decades of bad decisions – or counteract irreversible changes in how business is done. In the early 2010s, GE pushed a big-data and analytics platform for the “industrial internet” that it called Predix, reportedly spending some $5 billion on it. That was much too little, much too late. In the meantime, Microsoft Corp. , Amazon.com Inc.  and others had grown into conglomerates for the new age, offering a suite of technology services much the way GE had long filled the basic needs of industry. (WSJ)
  • University of Washington study: Deep learning reveals 3D models of protein machines. Proteins are made up of strings of amino acid building blocks, but they need to fold correctly to work. IPD’s RoseTTAFold and DeepMind’s AlphaFold have been used to predict the shapes of thousands of proteins since their release. Inside cells, proteins often interact with each other in machine-like protein complexes that perform a variety of tasks. Many approved drugs also interfere with protein complexes, such as chemotherapies that hijack machinery involved in DNA replication and cell division. (GeekWire)
  • The Chip That Could Transform Computing. It was Intel’s co-founder Gordon Moore who famously predicted that computer chips would keep getting unimaginably more powerful. And it was Intel’s products, the x86 line of microprocessors at the heart of just about every personal computer, that turned Moore’s prophesy into a governing “law” of tech. The promise that every year, Intel’s new chips would be much faster than its old chips set the rhythm for advances across the entire industry. (NYT)
  • When algorithms go bad: Zillow, Amazon, Facebook and the pitfalls of rampant automation. The downfall of Zillow’s iBuying business is a reminder of the downsides of relying too much on automation and machine learning algorithms at this stage in the evolution of technology. (GeekWire)
  • Managing AI Decision-Making Tools. The nature of micro-decisions requires some level of automation, particularly for real-time and higher-volume decisions. Automation is enabled by algorithms (the rules, predictions, constraints, and logic that determine how a micro-decision is made). And these decision-making algorithms are often described as artificial intelligence (AI). The critical question is, how do human managers manage these types of algorithm-powered systems? (HBR)

Databricks vs Snowflake: Performance blog war!

Healthy and open competition is great for any industry, especially the technology industry that is super conscious of price/performance. Databricks and Snowflake are two great companies duking it out in this price/performance game recently. They’ve published blogs with claims and counter claims. Great insights provided by both blogs and interesting read as well. If you are too rushed to read the entire blog(s), the images below gives you a snapshot of what is said in the blogs. Enjoy!.

Earlier this month, Databricks published a blog claiming “World record” performance for processing 100TB tpc-ds benchmark. It also said corroboration by Barcelona supercomputing center (BCS). And squarely aimed it at Snowflake!https://databricks.com/blog/2021/11/02/databricks-sets-official-data-warehousing-performance-record.html

Chart 1: Elapsed time for test derived from TPC-DS 100TB Power Run, by Barcelona Supercomputing Center.

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Chart 2: Price/Performance for test derived from TPC-DS 100TB Power Run, by Barcelona Supercomputing Center.

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Yesterday, Snowflake published a counter blog (written by the founders benoit and thierry). Basically says, you don’t need a third party, just do it yourself in our cloud platform, it is so simple to verify!!.https://www.snowflake.com/blog/industry-benchmarks-and-competing-with-integrity/

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