Is Stagflation Here: Comparing The 2020s With The 1970s…
Is Stagflation Here: Comparing The 2020s With The 1970s…
Now that the fear of stagflation is a growing concern on Wall Street as the latest BofA Fund Manager Survey showed…
… as the inflation debate – at a time of shrinking global…
Now that the fear of stagflation is a growing concern on Wall Street as the latest BofA Fund Manager Survey showed...
... as the inflation debate - at a time of shrinking global growth - has taken on renewed vigor given the latest commodity price surge over recent weeks, the energy shocks and discussions around stagflation have led many to make the comparison to the 1970s not just on this site...
If this guy is right, there will be 1970s style mass shortages of most products in a few months https://t.co/7vpfupqhEj— zerohedge (@zerohedge) April 28, 2021
... but elsewhere:
- Paul Tudor Jones, CEO of Tudor Investment Corp., tells CNBC that inflation is the single biggest threat to the economy: "The inflation genie is out of the bottle and we run the risk of returning to the 1970s" - CNBC
- Is Stagflation Coming Back? Economist Sees Parallels With the 1970s—and Big Differences - Barrons
- Is the world economy going back to the 1970s? - The Economist
- What the Inflation of the 1970s Can Teach Us Today - WSJ
- Conditions are ripe for repeat of 1970s stagflation - Guardian
- Ignore the fearmongers: the 1970s are not coming back - Guardian
- A Stock Market Malaise With the Shadow of ’70s-Style Stagflation - NYT
Addressing these growing comparisons between the 2020s and the 1970s, last week Deutsche Bank's credit strategists Henry Allen and Jim Reid looked into some of the similarities and differences between that infamous inflationary decade and today. Below we summarize some of the key observations made by the duo, who looked at how the 1970s evolved from an inflationary perspective and compare and contrast to today.
We start by reminding readers that things were very bad in the 1970s....
As Deutsche Bank writes, TV screens in the UK have recently shown scenes of long lines for gas across the vast majority of fuelling stations. Initially, this wasn’t about a shortage of fuel, but a shortage of HGV drivers that fed upon itself to become a fuel shortage amidst a demand surge as well. Right now, we’re still a long way from what we saw in the 1970s, when there were big reductions in the supply of energy, but the recent rise in global gas prices could be much more troublesome going forward. Across the globe, fuel rationing took place for a period of time back then, and governments ran huge media campaigns to conserve energy. President Nixon asked gas stations not
to sell gasoline on Saturday or Sunday nights, and eventually license plate restrictions (odd and even) were in place in the US for when you could buy fuel. In Europe, some examples of the stresses included a ban in the Netherlands on Sunday driving, whilst the UK imposed a 3-day week as coal shortages threatened electricity supplies alongside a winter series of strikes by coal miners and rail workers. Households were asked to heat only one room in their homes.
so we need to put into perspective how bad things got for individuals and economies due to the energy issues. The recent gas problems have raised the prospects of a winter where rationing could take place but this is speculation for now. However, the spikes in gas prices are reminiscent of what happened with oil in the early 1970s (both have a geopolitical angle too) so some historical awareness is useful.
How did inflation get out of control in the 1970s?
Today’s situation has a number of parallels to what happened in the 1960s and 1970s, when inflation gradually accelerated to the point where it was out of control. Various shocks coalesced over a short period of time, and policymakers were consistently behind the curve in reacting:
- In the US, the Johnson Administration’s Great Society programs and the Vietnam War drove up fiscal spending in the late-1960s.
- In 1971, President Nixon ended the dollar’s link to gold, ending the system of fixed exchange rates that had prevailed after the Second World War.
- An El Nino event in 1972 drove up food prices.
- The dollar underwent a devaluation in February 1973.
- Then on top of all this, the first oil shock occurred in 1973, followed by a second oil shock in 1979.
Even though the commodity shocks are generally held most responsible for the high inflation over the period, it’s clear that inflation was already embedded in the system well before they occurred. So if you were keeping a strict timeline you could argue that when it comes to economic policy being more expansionary, we’re more in the late-1960s than the 1970s. Perhaps Covid has made the timeline more compressed, but inflation steadily moved from under 2% in the first half of the 60s to over 6% by the end of the decade.
The inflationary set up in the 70s then deteriorated thanks to the suspension of the dollar’s convertibility into gold in 1971. Given that virtually every other currency was fixed to the dollar at the time, we quickly moved from a world of gold-based money to one where fiat money was in control. Interestingly, Figure 1 shows that with this loosening of policy constraints, the YoY percentage growth in monetary aggregates moved consistently into the low teens from high single digits in the late 1960s.
Today, we’ve moved from pre-covid mid-single digit YoY percentage growth to a brief period of 25% YoY growth at the peak. Even if we revert back to single digit percentage growth there’s still a large residual amount of liquidity in the economy far above that assumed by the pre-covid trend. So there’s been a faster injection of money into the economy in the space of a year than we saw at any point in the 1970s.
But even as inflation continuously accelerated through the late-1960s onwards, central bankers found it difficult to shift policy in a hawkish direction. This was partly down to political pressure, both explicit and implicit, since politicians were not keen on the idea of a slowdown in growth and higher unemployment. It was also down to a poor understanding of the economy - with policymakers wrongly believing in the Phillips Curve, and the belief that it was possible to “buy” lower unemployment with higher inflation, when this wasn’t actually true over the long term.
We can see some of this pressure in action by looking back through the archives. The following quote comes from the Fed’s senior economist, J. Charles Partee, in the memorandum of discussion from the March 1973 FOMC meeting. He said that “To adopt a substantially more restrictive policy that carries with it the danger of stagnation or recession would seem unreasonable and counterproductive. As unemployment rose, there would be strong social and political pressure for expansive actions, so that the policy would very likely have to be reversed before it succeeded in tempering either the rate of inflation or the underlying sources of inflation.”
So even the Fed’s economists at the time were acknowledging the “social and political pressure” under which they were operating. One more recent academic paper by Charles Weise (2012) actually found that references at FOMC meetings to the political environment were correlated with the stance of monetary policy, which further suggests it was having an impact on decision-making.
Another serious issue was that the Fed was operating with a poor understanding of the available data. Orphanides (2002) notes that errors in the assessment of the natural rate of unemployment meant policymakers believed that the economy was operating beneath potential. So that helped to justify lower interest rates than prevailed in reality. Had they actually realized the situation as it prevailed at the time, then perhaps they would have pushed more strongly for a hawkish stance. So a number of factors were pushing inflation higher. But what turbocharged it into double-digits in the US were two major oil shocks, which had ramifications across the entire developed world?
1973: The First Oil Shock
The first oil shock was triggered by the Organization of Arab Petroleum Exporting Countries (OAPEC) placing an embargo on a number of countries, including the United States, in retaliation for their support for Israel in the Yom Kippur War. There is also some evidence that the US abandoning the convertibility of the dollar into gold, which led to a big devaluation of the dollar, and a loss of income for oil producers, helped create resentment from this group.
Regardless of the cause, this led to a quadrupling in oil prices, triggering a recession across multiple countries that began in late 1973. Inflation was already running at a decent clip, but this turbocharged it, with CPI peaking at 12.2%, which was the highest it had been since the immediate aftermath of WWII.
This, as Deutsche Bank notes, posed a tricky dilemma for the Federal Reserve. Although the inflation rate was high and rising, unemployment was also climbing at the same time. So hiking rates to deal with inflation risked exacerbating the unemployment situation. This scenario is completely unlike what happened after the GFC in 2008, which was a big deflationary shock, making it clear which way the Fed needed to move rates.
At the time, the view was that the embargo was a structural shock that monetary policy couldn’t affect, so it should therefore look through such a transitory factor (this should ring a few bells). For a fly-on-the-wall view, Stephen Roach, who’s now a Senior Fellow at Yale but was formerly on the research staff at the Fed, said that Fed Chair Burns argued that as the shock had nothing to do with monetary policy, the Fed should exclude oil and energy-related products from the CPI index for its analysis. Roach then said Burns insisted on removing food prices in 1973 after unusual weather. This too should ring bells... and alarms.
The exclusions of these “transitory” factors became so extreme that Roach estimates that only 35% of the CPI basket was left. By the middle of the decade this series itself was then rising at a double-digit rate. You can get a sense of how loose policy was here by looking at the real Federal Funds rate, which moved into negative territory as a result of the oil shock. Interestingly, the real rate is now even lower than it was at any point in the 1970s.
To be fair to the Fed, at the start of the energy shock it would have been tough to know how the situation would develop. The record from the December 1973 Fed meeting says: “On balance, the Chairman concluded, he believed that some easing of monetary policy was indicated today, but that it should take the form of a modest and cautious step. He was aware of the possibility that the oil embargo might not last more than another few weeks. On the other hand, the embargo might last another year.” So although we can view events with a detached level of hindsight, with the knowledge of how they played out, they were living through this in real time.
As it happened, the embargo lasted until the following March, but the long-term effects are still with us today. The shock had revealed the dependence of the United States and others on foreign oil, so an emphasis was placed on reducing that dependence. That saw the Strategic Petroleum Reserve created in the US in 1975, which is a tool that today’s Energy Secretary has said is under consideration to deal with the present energy price surge. Then in 1977, the Department of Energy was created, which is also with us to this day.
As Figure 4 shows, US inflation did come down again once the worst of the first oil shock had passed. But it only fell back to around 5% before picking up again, whilst monetary policy still remained fairly accommodative to deal with high unemployment (Figure 5), which in December 1976 stood at 7.8%.
This was partly because there was still political pressure on the Fed. The Carter Administration arrived in office at the start of 1977, and in the transcript of the FOMC meeting that January, Chairman Burns said “We have a new Administration; the new Administration has proposed a fiscal plan for reducing unemployment, and any lowering of monetary growth rates at this time would, I’m quite sure, be very widely interpreted--and not only in the political arena--as an attempt on the part of the Federal Reserve to frustrate the efforts of a newly elected President and newly elected Congress to get our economy, to use a popular phrase, “moving once again.”
Fast forward to today and although there isn’t the same level of political concern, the Fed have recently undertaken a dovish shift following their recent policy review. Their move towards average inflation targeting is an explicit acknowledgement that they’re willing to accept above-target inflation to make up for past undershoots. Furthermore, they have adopted a much more tolerant view on the risk of
inflationary pressures from low unemployment, and officials regularly discuss distributional issues such as economic performance for those on low incomes or minority groups. So it’s clear that the Fed’s reaction function has changed relative to where it was just a few years ago.
1979: The Second Oil Shock
Back to the 70s and just as the economy was recovering from the effects of the 1973 shock, a second oil shock in 1979 sent inflation sharply higher once again. This took place around the time of the Iranian revolution, which coincided with a big decline in Iranian oil output, to the tune of around 7% of global production at the time. Then in 1980, the Iran-Iraq War caused further declines in production for both countries.
Although plenty blame the oil shock for creating high inflation, the truth was that this was merely the final nail in the coffin for the old regime, since in the preceding years, the Fed had persistently underestimated how high inflation would rise. The next chart shows that the Fed’s staff forecasts were repeatedly upgraded as time went on, even prior to the second shock.
Unlike in 1973 however, this shock induced a much more hawkish policy response from the new Fed Chair Paul Volcker. Indeed, the transcript from Volcker’s first meeting as Fed Chair in August 1979 shows him pointing to higher inflation expectations that had developed, saying that “I think people are acting on that expectation [of continued high inflation] much more firmly than they used to.” And Volcker also recognized that restoring the credibility of economic policy could also “buy some flexibility in the future”.
Although higher rates were a contributory factor behind the recession that began in early 1980, this new pro-active approach was successful at containing inflation, which fell from a peak of 14.6% in March 1980, down to 2.4% in July 1983. The real Fed Funds rate turned sharply positive in the early 1980s, dramatically above levels seen in the mid-1970s (see Figure 3). To this day, US inflation has yet to rise above 7% again.
Comparing the 1970s and the 2020s: can we expect a repeat?
Having discussed the 1970s, Deutsche notes that one of the biggest questions on investors’ minds is whether we’re in for a repeat. Some factors like demographics or globalization indicate that there are much greater inflationary pressures today. But others like declining union power and lower energy intensity are pointing in the other direction. We now look at a number of these in turn.
1. Monetary Policy
Like the 1970s, monetary policy is very loose today. In fact, the real federal funds rate (simply found by subtracting 12-month CPI inflation as per Figure 3) is actually lower today than it was then, while the increase in the money stock (Figure 1) has also seen a much bigger single year expansion than ever took place in the 1970s. Financial conditions today remain accommodative as well, thus providing a lot of support for the economy.
Recent decades have seen an extraordinary increase in global debt levels. In particular, government debt levels today are well in excess of the low levels reached in the 1970s. As a consequence, higher rates will have a much bigger impact on government and non-government balance sheets, and risk being much tougher to stomach today than they were then. This could mean policy makers are forced to remain behind the curve in a similar way to the 1970s, albeit for different reasons.
The consensus assumes that demographics will be disinflationary as societies age. However, one similarity between the 1970s and now could be a worker shortage, albeit from different sides of the baby boomer demographic miracle. In the 1970s, the boomers had yet to hit the workforce and labor was relatively scarce. But from the 1980s onwards, the global labor force exploded in size as the boomers came of age. Simultaneously, China began to integrate itself into the global economy for the first time in several generations, thus unleashing a big positive labor supply shock onto the global economy. This combination has been disinflationary for wages for the past four decades. However, the major economies are now set to see their labor forces decline or at best level off as the baby boomers retire. So will we get similar labor market pressures as seen in the 1970s? Covid has shown what can happen to wages when there is a shortage of labor. The huge number of vacancies in low-paid jobs today due to a shortage of workers due to covid related issues are pushing wages up. And although the covid bottleneck will clear, the declining working-age population in many places over the decade ahead could see labor gain back some power that it lost from the end of the 1970s.
The late-20th century was an era of rising globalization, with the 1970s alone seeing the share of global trade in GDP rise from 27% in 1970 to 39% by 1980. But since 2008, that progressive advance has stalled, and there are many signs that the post-pandemic will see a return to less globalization, as both countries and corporates look to localize their supply chains in order to make them more resilient. In turn, a retreat from globalization and firms facing less competition implies higher prices than would otherwise be the case. So as with demographics, the potential retreat of globalization would remove another of the big forces that’s helped to suppress inflation over recent decades.
All the factors mentioned above point towards inflation being more difficult to combat today. But there are others that point in the opposite direction.
5. Energy Reliance
Since the 1970s, the US economy has become progressively less energy intensive. By 2020, the amount of energy required for each unit of GDP was just 37% of where it had been back in 1970, and the US Energy Information Agency are forecasting that will continue to fall over the coming decades. So with less energy required to support output, the impact of a price shock will be commensurately less than it was back in the Great Inflation of the 1970s.
6. Union Power
Another force acting against inflation is the decline in union membership over recent decades. Unions themselves do not cause inflation, which is a monetary phenomenon, but they can contribute to wage-price spirals. This is because higher inflation leads to higher wage demands from trade unions to ensure their members’ wages keep up with the rising cost of living. But firms then anticipate this by bidding up their own prices further, which can create a circular feedback loop as the unions in turn demand higher wages still. So the fact that unions are weaker is likely to put downward pressure on inflation, all other things equal. Having said this, there is some evidence that unionization is on an increasing trend, albeit from a low base. The mention of unions in official company documents was the fastest growing of our ESG buzz words in September 2021 relative to a year earlier.
7.War, Geopolitics and Climate Change
Many of the biggest inflations in history have been associated with wars, and the inflation of the 1960s and 1970s got going around the time of the Vietnam War, when there was upward pressure on spending. Today, the economic response to Covid has been almost comparable, with fiscal deficits on a scale not seen since WWII for many countries. In addition, the geopolitics of Russia being such an important supplier of gas to Europe has parallels with the West’s reliance on Middle Eastern oil supplies in the 1970s at a time of a divisive Arab/Israeli conflict.
Going forward, the US/China relationship could be a key driver of inflation later in the current decade, particularly if an escalating cold war leads to a more bipolar world and a retreat from globalization, as discussed earlier. And that’s before we get onto the threat of climate change, where we’re already seeing the consequence of trying to move away from coal, in that we’ve become more dependent on other fuel sources such as natural gas. As the globe tries to further wean itself off fossil fuels, we could have more energy shocks over the course of this decade.
8. The lessons of history
Finally, history itself plays an important role in policymaking. For example, part of the reason that the economic response to the pandemic was so large and swift was in order to avoid repeating the mistakes of the global financial crisis, where delays undermined the recovery.
When it comes to inflation in 2021, plenty have raised concerns that today’s policymakers have little to no experience of dealing with a significant inflation problem. Indeed, for the decade after 2008, the main focus was on how to tackle chronically deficient demand as central bankers struggled to hit their inflation targets on a sustained basis in many countries. So the fear is that policymakers might have a dovish bias given these experiences, and risk being slow to recognize if inflation has become a more permanent feature of the landscape. This is particularly so when if anything, the perception is that they were too hawkish in the period following the financial crisis.
On the other hand, today’s central bankers and other policymakers are aware of the lessons of the 1970s and will not want their legacies to involve a repeat. They recognize that inflation and unemployment can’t be traded off against each other over the longer term, and have much better data than their predecessors. Furthermore, there is still strong political pressure to avoid higher inflation... even as there is even greater political pressure to avoid taking the much needed if very painful steps to contain the coming inflation.
What can we learn from this?
Looking at the 1970s, the most important lesson is that even if inflation is down to transitory factors, the arrival of yet more “transitory” shocks can accumulate to keep inflation at high levels, with expectations becoming unanchored. That was what occurred with the oil shocks: although inflation was sent sharply higher, the truth is that inflation was pretty high already, as a legacy from the late 1960s, and the shocks turbocharged it yet further.
But we can view the events of the 1970s with the benefit of hindsight. For policymakers at the time, it was less obvious that these shocks would not prove transitory, and today they face a similar dilemma. If policy reacts too forcefully to something central banks can’t control (like inflation thanks to supply-chain disruptions), then that risks undermining the recovery and actually pushing inflation below target, since the shock will eventually pass and monetary policy operates with a lag. On the other hand, doing nothing risks inflation expectations becoming unanchored, particularly if another shock then arrives to push inflation higher still. One can also argue that with money supply growth so strong over the past 18 months, there has been a strong monetary angle to inflation and therefore some tightening of monetary policy is sensible. Overall, it is an unenviable dilemma, and the debate in the economics profession right now speaks to the unknowns.
So we approach this question with some humility. But we do think it worth noting that many factors like debt, demographics and globalisation all indicate that we could be facing an even more difficult situation than we saw back then. And the monetary aggregates have also seen a much more rapid increase as well. So policymakers will need to be vigilant for a potential repeat, particularly given that the institutional memories of high inflation have faded over time.
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Spread & Containment
Asking the right dumb questions
You’ll have to forgive the truncated newsletter this week. Turns out I brought more back from Chicago than a couple of robot stress balls (the one piece…
You’ll have to forgive the truncated newsletter this week. Turns out I brought more back from Chicago than a couple of robot stress balls (the one piece of swag I will gladly accept). I was telling someone ahead of the ProMat trip that I’ve returned to 2019 travel levels this year. One bit I’d forgotten was the frequency and severity of convention colds — “con crud,” as my comics friends used to call it.
I’ve been mostly housebound for the last few days, dealing with this special brand of Chicago-style deep-dish viral infection. The past three years have no doubt hobbled my immune system, but after catching COVID-19 three times, it’s frankly refreshing to have a classic, good old-fashioned head cold. Sometimes you want the band you see live to play the hits, you know? I’m rediscovering the transformative properties of honey in a cup of tea.
The good news for me is that (and, hopefully, you) is I’ve got a trio of interviews from ProMat that I’ve been wanting to share in Actuator. As I said last week, the trip was really insightful. At one of the after-show events, someone asked me how one gets into tech journalism. It’s something I’ve been asked from time to time, and I always have the same answer. There are two paths in. One is as a technologist; the other is as a journalist.
It’s obvious on the face of it. But the point is that people tend to enter the field in one of two distinct ways. Either they love writing or they’re really into tech. I was the former. I moved to New York City to write about music. It’s something I still do, but it’s never fully paid the bills. The good news for me is I sincerely believe it’s easier to learn about technology than it is to learn how to be a good writer.
I suspect the world of robotics startups is similarly bifurcated. You enter as either a robotics expert or someone with a deep knowledge of the field that’s being automated. I often think about the time iRobot CEO Colin Angle told me that, in order to become a successful roboticist, he first had to become a vacuum salesman. He and his fellow co-founders got into the world through the robotics side. And then there’s Locus robotics, which began as a logistics company that started building robots out of necessity.
Both approaches are valid, and I’m not entirely sure one is better than the other, assuming you’re willing to surround yourself with assertive people who possess deep knowledge in areas where you fall short. I don’t know if I entirely buy the old adage that there’s no such thing as a dumb question, but I do believe that dumb questions are necessary, and you need to get comfortable asking them. You also need to find a group of people you’re comfortable asking. Smart people know the right dumb questions to ask.
Covering robotics has been a similar journey for me. I learned as much about supply chain/logistics as the robots that serve them at last week’s event. That’s been an extremely edifying aspect of writing about the space. In robotics, no one really gets to be a pure roboticist anymore.
Q&A with Rick Faulk
I’m gonna kick things off this week with highlights from a trio of ProMat interviews. First up is Locus Robotics CEO, Rick Faulk. The full interview is here.
TC: You potentially have the foundation to automate the entire process.
RF: We absolutely do that today. It’s not a dream.
It’s not lights out. Lights out might happen 10 years from now, but the ROI is not there to do it today. It may be there down the road. We’ve got advanced product groups working on some things that are looking at how to get more labor out of the equation. Our strategy is to minimize labor over time. We’re doing integrations with Berkshire Grey and others to minimize labor. To get to a dark building is going to be years away.
Have you explored front-of-house — retail or restaurants?
We have a lot of calls about restaurants. Our strategy is to focus. There are 135,000 warehouses out there that have to be automated. Less than 5% are automated today. I was in Japan recently, and my meal was filled by a robot. I look around and say, “Hey, we could do that.” But it’s a different market.
What is the safety protocol? If a robot and I are walking toward each other on the floor, will it stop first?
It will stop or they’ll navigate around. It’s unbelievably smart. If you saw what happened on the back end — it’s dynamically planning paths in real time. Each robot is talking to other robots. This robot will tell this robot over here, “You can’t get through here, so go around.” If there’s an accident, we’ll go around it.
They’re all creating a large, cloud-based map together in real time.
That’s exactly what it is.
When was the company founded?
[In] 2014. We actually spun out of a company called Quiet Logistics. It was a 3PL. We were fully automated with Kiva. Amazon bought Kiva in 2012, and said, “We’re going to take the product off the market.” We looked for another robot and couldn’t find one, so we decided to build one.
The form factors are similar.
Their form factor is basically the bottom. It goes under a shelf and brings the shelf back to the station to do a pick. The great thing about our solution is we can go into a brownfield building. They’re great and they work, but it will also take four times the number of robots to do the same work our robots do.
Amazon keeps coming up in my conversations in the space as a motivator for warehouses to adopt technologies to remain competitive. But there’s an even deeper connection here.
Amazon is actually our best marketing organization. They’re setting the bar for SLAs (service-level agreements). Every single one of these 3PLs walking around here [has] to do same- or next-day delivery, because that’s what’s being demanded by their clients.
Do the systems’ style require in-person deployment?
The interesting thing during COVID is we actually deployed a site over FaceTime.
Someone walked around the warehouse with a phone?
Yeah. It’s not our preferred method. They probably actually did a better job than we did. It was terrific.
As far as efficiency, that could make a lot of sense, moving forward.
Yeah. It does still require humans to go in, do the installation and training — that sort of thing. I think it will be a while before we get away from that. But it’s not hard to do. We take folks off the street, train them and in a month they know how to deploy.
Where are they manufactured?
We manufacture them in Boston, believe it or not. We have contract manufacturers manufacturing some components, like the base and the mast. And then we integrate them together in Boston. We do the final assembly and then do all the shipments.
As you expand sales globally, are there plans to open additional manufacturing sites?
We will eventually. Right now we’re doing some assemblies in Amsterdam. We’re doing all refurbishments for Europe in Amsterdam. […] There’s a big sustainability story, too. Sustainability is really important to big clients like DHL. Ours is an inherently green model. We have over 12,000 robots in the field. You can count the number of robots we’ve scrapped on two hands. Everything gets recycled to the field. A robot will come back after three or four years and we’ll rewrap it. We may have to swap out a camera, a light or something. And then it goes back into service under a RaaS model.
What happened in the cases where they had to be scrapped?
They got hit by forklifts and they were unrepairable. I mean crushed.
Any additional fundraising on the horizon?
We’ve raised about $430 million, went through our Series F. Next leg in our financing will be an IPO. Probably. We have the numbers to do it now. The market conditions are not right to do it, for all the reasons you know.
Do you have a rough timeline?
It will be next year, but the markets have got to recover. We don’t control that.
Q&A with Jerome Dubois
Next up, fittingly, is Jerome Dubois, the co-founder of Locus’ chief competitor, 6 River Systems (now a part of Shopify). Full interview here.
TC: Why was [the Shopify acquisition] the right move? Had you considered IPO’ing or moving in a different direction?
JD: In 2019, when we were raising money, we were doing well. But Shopify presents itself and says, “Hey, we’re interested in investing in the space. We want to build out a logistics network. We need technology like yours to make it happen. We’ve got the right team; you know about the space. Let’s see if this works out.”
What we’ve been able to do is leverage a tremendous amount of investment from Shopify to grow the company. We were about 120 employees at 30 sites. We’re at 420 employees now and over 110 sites globally.
Amazon buys Kiva and cuts off third-party access to their robots. That must have been a discussion you had with Shopify.
Up front. “If that’s what the plan is, we’re not interested.” We had a strong positive trajectory; we had strong investors. Everyone was really bullish on it. That’s not what it’s been. It’s been the opposite. We’ve been run independently from Shopify. We continue to invest and grow the business.
From a business perspective, I understand Amazon’s decision to cut off access and give itself a leg up. What’s in it for Shopify if anyone can still deploy your robots?
Shopify’s mantra is very different from Amazon. I’m responsible for Shopify’s logistics. Shopify is the brand behind the brand, so they have a relationship with merchants and the customers. They want to own a relationship with the merchant. It’s about building the right tools and making it easier for the merchant to succeed. Supply chain is a huge issue for lots of merchants. To sell the first thing, they have to fulfill the first thing, so Shopify is making it easier for them to print off a shipping label.
Now, if you’ve got to do 100 shipping letters a day, you’re not going to do that by yourself. You want us to fulfill it for you, and Shopify built out a fulfillment network using a lot of third parties, and our technology is the backbone of the warehouse.
Watching you — Locus or Fetch — you’re more or less maintaining a form factor. Obviously, Amazon is diversifying. For many of these customers, I imagine the ideal robot is something that’s not only mobile and autonomous, but also actually does the picking itself. Is this something you’re exploring?
Most of the AMR (autonomous mobile robot) scene has gotten to a point where the hardware is commoditized. The robots are generally pretty reliable. Some are maybe higher quality than others, but what matters the most is the workflows that are being enacted by these robots. The big thing that’s differentiating Locus and us is, we actually come in with predefined workflows that do a specific kind of work. It’s not just a generic robot that comes in and does stuff. So you can integrate it into your workflow very quickly, because it knows you want to do a batch pick and sortation. It knows that you want to do discreet order picking. Those are all workflows that have been predefined and prefilled in the solution.
With respect to the solving of the grabbing and picking, I’ve been on the record for a long time saying it’s a really hard problem. I’m not sure picking in e-comm or out of the bin is the right place for that solution. If you think about the infrastructure that’s required to solve going into an aisle and grabbing a pink shirt versus a blue shirt in a dark aisle using robots, it doesn’t work very well, currently. That’s why goods-to-person makes more sense in that environment. If you try to use arms, a Kiva-like solution or a shuttle-type solution, where the inventory is being brought to a station and the lighting is there, then I think arms are going to be effective there.
Are these the kinds of problems you invest R&D in?
Not the picking side. In the world of total addressable market — the industry as a whole, between Locus, us, Fetch and others — is at maybe 5% penetration. I think there’s plenty of opportunity for us to go and implement a lot of our technology in other places. I also think the logical expansion is around the case and pallet operations.
Interoperability is an interesting conversation. No one makes robots for every use case. If you want to get near full autonomous, you’re going to have a lot of different robots.
We are not going to be a fit for 100% of the picks in the building. For the 20% that we’re not doing, you still leverage all the goodness of our management consoles, our training and that kind of stuff, and you can extend out with [the mobile fulfillment application]. And it’s not just picking. It’s receiving, it’s put away and whatever else. It’s the first step for us, in terms of proving wall-to-wall capabilities.
What does interoperability look like beyond that?
We do system interoperability today. We interface with automation systems all the time out in the field. That’s an important part of interoperability. We’re passing important messages on how big a box we need to build and in what sequence it needs to be built.
When you’re independent, you’re focused on getting to portability. Does that pressure change when you’re acquired by a Shopify?
I think the difference with Shopify is, it allows us to think more long-term in terms of doing the right thing without having the pressure of investors. That was one of the benefits. We are delivering lots of longer-term software bets.
Q&A with Peter Chen
Lastly, since I’ve chatted with co-founder Pieter Abbeel a number of times over the years, it felt right to have a formal conversation with Covariant CEO Peter Chen. Full interview here.
TC: A lot of researchers are taking a lot of different approaches to learning. What’s different about yours?
PC: A lot of the founding team was from OpenAI — like three of the four co-founders. If you look at what OpenAI has done in the last three to four years to the language space, it’s basically taking a foundation model approach to language. Before the recent ChatGPT, there were a lot of natural language processing AIs out there. Search, translate, sentiment detection, spam detection — there were loads of natural language AIs out there. The approach before GPT is, for each use case, you train a specific AI to it, using a smaller subset of data. Look at the results now, and GPT basically abolishes the field of translation, and it’s not even trained to translation. The foundation model approach is basically, instead of using small amounts of data that’s specific to one situation or train a model that’s specific to one circumstance, let’s train a large foundation-generalized model on a lot more data, so the AI is more generalized.
You’re focused on picking and placing, but are you also laying the foundation for future applications?
Definitely. The grasping capability or pick and place capability is definitely the first general capability that we’re giving the robots. But if you look behind the scenes, there’s a lot of 3D understanding or object understanding. There are a lot of cognitive primitives that are generalizable to future robotic applications. That being said, grasping or picking is such a vast space we can work on this for a while.
You go after picking and placing first because there’s a clear need for it.
There’s clear need, and there’s also a clear lack of technology for it. The interesting thing is, if you came by this show 10 years ago, you would have been able to find picking robots. They just wouldn’t work. The industry has struggled with this for a very long time. People said this couldn’t work without AI, so people tried niche AI and off-the-shelf AI, and they didn’t work.
Your systems are feeding into a central database and every pick is informing machines how to pick in the future.
Yeah. The funny thing is that almost every item we touch passes through a warehouse at some point. It’s almost a central clearing place of everything in the physical world. When you start by building AI for warehouses, it’s a great foundation for AI that goes out of warehouses. Say you take an apple out of the field and bring it to an agricultural plant — it’s seen an apple before. It’s seen strawberries before.
That’s a one-to-one. I pick an apple in a fulfillment center, so I can pick an apple in a field. More abstractly, how can these learnings be applied to other facets of life?
If we want to take a step back from Covariant specifically, and think about where the technology trend is going, we’re seeing an interesting convergence of AI, software and mechatronics. Traditionally, these three fields are somewhat separate from each other. Mechatronics is what you’ll find when you come to this show. It’s about repeatable movement. If you talk to the salespeople, they tell you about reliability, how this machine can do the same thing over and over again.
The really amazing evolution we have seen from Silicon Valley in the last 15 to 20 years is in software. People have cracked the code on how to build really complex and highly intelligent looking software. All of these apps we’re using [are] really people harnessing the capabilities of software. Now we are at the front seat of AI, with all of the amazing advances. When you ask me what’s beyond warehouses, where I see this really going is the convergence of these three trends to build highly autonomous physical machines in the world. You need the convergence of all of the technologies.
You mentioned ChatGPT coming in and blindsiding people making translation software. That’s something that happens in technology. Are you afraid of a GPT coming in and effectively blindsiding the work that Covariant is doing?
That’s a good question for a lot of people, but I think we had an unfair advantage in that we started with pretty much the same belief that OpenAI had with building foundational models. General AI is a better approach than building niche AI. That’s what we have been doing for the last five years. I would say that we are in a very good position, and we are very glad OpenAI demonstrated that this philosophy works really well. We’re very excited to do that in the world of robotics.
News of the week
The big news of the week quietly slipped out the day after ProMat drew to a close. Berkshire Grey, which had a strong presence at the event, announced on Friday a merger agreement that finds SoftBank Group acquiring all outstanding capital stock it didn’t already own. The all-cash deal is valued at around $375 million.
The post-SPAC life hasn’t been easy for the company, in spite of a generally booming market for logistics automation. Locus CEO Rick Faulk told me above that the company plans to IPO next year, after the market settles down. The category is still a young one, and there remains an open question around how many big players will be able to support themselves. For example, 6 River Systems and Fetch have both been acquired, by Shopify and Zebra, respectively.
“After a thoughtful review of value creation opportunities available to Berkshire Grey, we are pleased to have reached this agreement with SoftBank, which we believe offers significant value to our stockholders,” CEO Tom Wagner said in a release. “SoftBank is a great partner and this merger will strengthen our ability to serve customers with our disruptive AI robotics technology as they seek to become more efficient in their operations and maintain a competitive edge.”
Unlike the Kiva deal that set much of this category in motion a decade ago, SoftBank maintains that it’s bullish about offering BG’s product to existing and new customers. Says managing partner, Vikas J. Parekh:
As a long-time partner and investor in Berkshire Grey, we have a shared vision for robotics and automation. Berkshire Grey is a pioneer in transformative, AI-enabled robotic technologies that address use cases in retail, eCommerce, grocery, 3PL, and package handling companies. We look forward to partnering with Berkshire Grey to accelerate their growth and deliver ongoing excellence for customers.
A healthy Series A this week from Venti Technologies. The Singapore/U.S. firm, whose name translates to “large Starbucks cup,” raised $28.8 million, led by LG Technology Ventures. The startup is building autonomous systems for warehouses, ports and the like.
“If you have a big logistics facility where you run vehicles, the largest cost is human capital: drivers,” co-founder and CEO Heidi Wyle tells TechCrunch. “Our customers are telling us that they expect to save over 50% of their operations costs with self-driving vehicles. Think they will have huge savings.”
This week in fun pivots, Neubility is making the shift from adorable last-mile delivery robots to security bots. This isn’t the company’s first pivot, either. Kate notes that it’s now done so five times since its founding. Fifth time’s the charm, right?
Neubility currently has 50 robots out in the world, a number it plans to raise significantly, with as many as 400 by year’s end. That will be helped along by the $2.6 million recently tacked onto its existing $26 million Series A.
Model-Prime emerged out of stealth this week with a $2.3 million seed round, bringing its total raise to $3.3 million. The funding was led by Eniac Ventures and featured Endeavors and Quiet Capital. The small Pittsburgh-based firm was founded by veterans of the self-driving world, Arun Venkatadri and Jeanine Gritzer, who were seeking a way to create reusable data logs for robotics companies.
The startup says its tech, “handles important tasks like pulling the metadata, automated tagging, and making logs searchable. The vision is to make the robotics industry more like web apps, or mobile apps, where it now seems silly to build your own data solution when you could just use Datadog or Snowflake instead.”
Saildrone, meanwhile, is showcasing Voyager, a 33-foot uncrewed water vehicle. The system sports cameras, radar and an acoustic system designed to map a body of water down to 900 feet. The company has been testing the boat out in the world since last February and is set to begin full-scale production at a rate of a boat a week.
Finally, some research out of MIT. Robust MADER is a new version of MADER, which the team introduced in 2020 to help drones avoid in-air collisions.
“MADER worked great in simulations, but it hadn’t been tested in hardware. So, we built a bunch of drones and started flying them,” says grad student Kota Kondo. “The drones need to talk to each other to share trajectories, but once you start flying, you realize pretty quickly that there are always communication delays that introduce some failures.”
The new version adds in a delay before setting out on a new trajectory. That added time will allow it to receive and process information from fellow drones and adjust as needed. Kondo adds, “If you want to fly safer, you have to be careful, so it is reasonable that if you don’t want to collide with an obstacle, it will take you more time to get to your destination. If you collide with something, no matter how fast you go, it doesn’t really matter because you won’t reach your destination.”
Here you go, way too fast. Don’t slow down, you’re gonna crash. Na-na-na-na-na-na-na-na-na. (Subscribe to Actuator!)
Asking the right dumb questions by Brian Heater originally published on TechCrunchtesting covid-19 singapore japan europe
Cuban election: high turnout despite opposition call for boycott
Cubans turned out in higher numbers than expected at the recent elections.
Results of the five-yearly Cuban national assembly elections on March 26 will have disappointed opposition figures, who had called for a boycott to signal unhappiness with the government’s performance.
Two-thirds of the electorate submitted valid votes (that were not spoiled nor blank) despite opposition calls for people to stay away. Given all the difficulties and tensions of the past few years, the high numbers of voters seems to suggest that, although it is under strain, the Cuban political system is more resilient than expected. Turnout had been dropping since the days of former leader Fidel Castro, and poor voter numbers could have signalled significant dissatisfaction with the current president, Miguel Díaz-Canel Bermúdez.
One of the reasons for the high turnout may be a sense of communal rejection of US threats to national sovereignty, the importance of which should not be ignored, according to historians such as Louis Pérez. Tightening of US sanctions has certainly contributed to everyday suffering and economic hardship. Another reason for a high turnout may be President Díaz-Canel Bermúdez’s efforts to push ahead with reforms, increasing accountability and creating more opportunities for private enterprise and participation in decision-making at local level.
The election results and turnout of 76% might also be interpreted as an indication that among the majority who still support the government even in the middle of the recession, there is an increased willingness to actively express preferences rather than offer unconditional loyalty. This shift is expressed in the growing proportion (up from 20% of valid votes in 2018 to 28% in 2023) who selected specific candidates from the list for their constituency, rather than fully complying with official encouragement to simply indicate acceptance of the complete slate.
The elections mark the end of the first term of Díaz-Canel Bermúdez, during which the population has suffered from a severe recession.
Since the last election in 2018, the country has witnessed a series of major disasters, including a plane crash, three hurricanes, three tropical storms, a tornado, a gas explosion that destroyed a hotel and a huge fire at the country’s main oil depot. But the economic impact of those disasters were dwarfed by two further blows: the COVID pandemic and, above all, US foreign policy towards Cuba.
Despite the development and successful roll-out of effective vaccines, the possibility of an economic bounce-back from the COVID-induced recession (an 11% fall in GDP) has been effectively blocked by unprecedented restrictions on Cuba’s access to international trade and finance resulting from US sanctions imposed by the Trump administration and maintained under Joe Biden’s presidency.
March 2023 election: type of vote
The effects of COVID and tightened US sanctions have combined with the sorry state of the country’s infrastructure. Another factor was caused by the price of food and energy imports soaring between 2020 and 2022, which resulted in power outages and food shortages. A 2021 currency reform exacerbated disruption and hardships by sparking an inflationary surge.
Read more: Cuba: why record numbers of people are leaving as the most severe economic crisis since the 1990s hits -- a photo essay
Long queues and a growing sense of frustration also contributed to unprecedented protests in mid-2021 and a record-breaking wave of emigration. In 2022, almost 250,000 people – over 2% of the population – are reported to have left for the US, including many of Cuba’s youngest and brightest.
How do elections work?
The Cuban electoral system was originally created as a “participatory” rather than “representative” system of democracy in an attempt to avoid the political conflict, violence, corruption and foreign interference experienced before the 1959 revolution, as described by political scientist William LeoGrande.
As the Cuban Communist party is the only legal political party, Cuban elections are not contests between parties. The 470 candidates for the national assembly do not represent the party. Instead, around half of them are representatives of municipal governments (themselves elected in municipal elections) and the rest are nominated by bigger organisations. These include neighbourhood committees, official trade unions, the women’s federation, students’ organisations and the small farmers’ association. Local electoral commissions then select one candidate for each seat from the list of nominated candidates. It is not a requirement for candidates, members of mass organisations or the electoral commission to be members of the party; however, many are, effectively making it impossible for self-proclaimed dissidents to be selected.
The local electoral commissions, whose members are selected from the mass organisations, are responsible for the organisation of the ballots and counting of the vote. Once selected, candidates must receive over 50% of valid votes to become a member of the national assembly. Voters can either accept all the candidates on the list for their constituency (a “united vote”) or select some and not others. Voting is secret and voluntary.
Over the years, and particularly over the past decade, efforts have been made to ensure that candidates are representative of the population. They include ministers, workers, farmers, educators, managers and health workers. The average age of candidates in 2023, at 46 years, is lower than previous elections, while the proportion who are non-white has increased (45% compared with 41% in 2018), and 53% are women.
The national turnout for these elections, confirmed by the national electoral commission, was 76%. Although this is above the turnout in legislative elections in the UK (67.3% in 2019) and US (at 62.8% of the voting age population in 2020 and 47.5% in 2022, according to the Pew Research Center), it is significantly less than the 86% recorded in the last national election in 2018. The abstention rate increased, from 14% registered electors in 2018 to 24% in 2023, and in blank or spoiled ballots, from 5.6% to 9.7%, a possible indication that the hardship of the past few years have taken their toll on public confidence in the government.
Díaz-Canel Bermúdez, who lacks the status and charisma of his predecessors Fidel Castro and his brother, Raúl Castro (who were both leaders of the 1959 revolution), will need to be alert to concerns of the electorate as he begins his second term. He will need to find ways to improve living standards quickly. He has pushed ahead with reforms to allow Cubans to create private companies, foster innovation through university-enterprise links, and devolve budgets and decision-making to enable municipal authorities to directly respond to local demands.
However, with inflation persisting and fiscal resources overstretched, his scope for macroeconomic stimulation is restricted. A major obstacle is the US government’s seeming commitment to retain the most important economic sanctions, but Díaz-Canel Bermúdez must prevent further erosion in confidence in Cuba’s government and its political system.
Emily Morris has received funding from University College London, the Ford Foundation and the British Embassy, Havana.recession pandemic us government trump gdp oil uk
Aspen looks to rebound in production and revenue after Covid-19
Last year, South African-based vaccine manufacturer Aspen Pharmacare was facing reports that it had not received a single order for its manufactured Covid-19…
Last year, South African-based vaccine manufacturer Aspen Pharmacare was facing reports that it had not received a single order for its manufactured Covid-19 shots and that manufacturing lines were sitting idle. But now the vaccine producer is looking to turn things around.
Aspen’s disclosure of its financial results in March unveiled that manufacturing revenue had decreased by 12% to R 603 million ($33.8 million), which Lorraine Hill, Aspen Group’s COO, said is attributable to lower Covid vaccine sales.
However, things were not all negative as Aspen said it was in negotiations with customers seeking to “secure a portion of Aspen’s sterile manufacturing capabilities.”
Aspen CEO Steven Saad said in a release:
The Group’s performance under challenging trading conditions was anticipated and is aligned to guidance previously shared for the first half of the financial year. Consistent with our previous communications, we are optimistic that the results for the second half of this financial year will not only exceed those reported for the first half but will also exceed those of the second half of the prior year.
Aspen had initially invested in three sterile manufacturing lines at its production site in Gqeberha, South Africa, and had plans to invest in two more production lines. The intention was to transition the manufacturing of its own anesthetic products from third-party producers to enhance the supply, Hill told Endpoints News in an email.
“The COVID pandemic, however, fast-tracked our plans to manufacture vaccines as we pivoted and re-prioritized in-housing our anesthetic products to manufacture the COVID vaccine,” Hill said.
Hill stated that in August of last year, Aspen entered a long-term agreement with India’s Serum Institute for Aspen to manufacture, market and eventually distribute four vaccines in Africa. The Serum Institute deal will also help Aspen gain further entry into the routine vaccine market, which has “sustainable” demand and can diversify the manufacturer’s portfolio, Hill told Endpoints.
“This is an important milestone as Aspen seeks to optimize our sterile manufacturing capacity in Gqeberha. The four products are Pneumococcal vaccine, Rotavirus vaccine, Polyvalent Meningococcal Vaccine and the Hexavalent Vaccine with transfer activities currently underway,” Hill said.
The company also secured agreements with the Bill & Melinda Gates Foundation and the Coalition for Epidemic Preparedness Innovations in the meantime. Hill added that the grant funding from these deals has helped to offset the production costs related to starting production of the Serum Institute vaccines.
Saad added in the release that Aspen expects the new manufacturing business to bring in around R 2 billion ($112 million) in 2024.vaccine pandemic covid-19 africa india
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