Article interessant sobre la creació de llocs de treball

Ramon Aymerich, publicat a La Vanguardia el 28 d'agost de 2010

El futuro del Jonathan
El reto urgente es crear empleo para recuperar a los menos formados para el mercado

Hasta que duró, el textil fue un gran invento. Permitió crear riqueza y dio empleo a centenares de miles de personas. Muchas de ellas sin formación. No es que hoy no haya empresas textiles, pero no son ya aquella industria de masas que ocupó a tanta gente hasta la década de los 70. Después, el sector fue pulverizado por la competencia asiática, como otras industrias manufactureras –el calzado, el juguete, la electrónica de consumo– que lo acompañaron en el cambio de siglo. Pero su declive hizo menos daño de lo imaginable. Al menos en términos de empleo. Porque la construcción y el inmobiliario vinieron a suplir el papel de gran empleador local que tenían las viejas manufacturas.

Se vive como se trabaja. La industria manufacturera socializó a mucha gente e incluso la aventuró en el asociacionismo y el sindicalismo. El inmobiliario descapitalizó otros sectores y encumbró a los más listos, y pillos. Y la construcción los contrató a todos, incluso a los que salieron peor parados de tanto fracaso escolar. El Jonathan, todos los Jonathans, tuvieron un lugar en el mundo: pudieron comprarse coche, tunearlo y pedir el crédito para el piso.

Pero en aquella transición de uno a otro sector, este país se perdió una reflexión importante: si esta va dejando de ser una economía de bajos salarios, habrá que ir pensando en cómo se mantiene tanto empleo y en cómo transforma el sistema educativo. No se hizo ni una cosa ni la otra. Y aquel despiste vuelve ahora como un bumerán. Porque el mayor problema de esta larga crisis es crear empleo, empleo para gente sin mucha formación, pero con un salario digno. Y hoy se crea poco empleo, y a muy lenta velocidad. Aquí y en Estados Unidos. Pero especialmente aquí.

En un artículo publicado en Business Week el pasado julio, Andy Groove, fundador de Intel, escribía sobre el coste de crear un empleo en el sector de las tecnologías de la información. En 1970, dice Groove, cada nuevo empleo en Intel costaba 1.000 dólares. Cuarenta años después, un nuevo empleo en Google cuesta diez veces más (en dólares constantes). Las empresas americanas, razona Groove, están perdiendo la batalla del empleo. "Las start up son algo maravilloso, pero no crean empleo... Es tan importante el momento mítico de creación en el garaje como el paso del prototipo a la producción de masas". Parte de la causa está en la rapidez con la que China absorbe todo ese empleo. Esta misma semana, Foxconn, proveedora taiwanesa de empresas como Apple, ha anunciado que contratará 400.000 personas en los próximos doce meses (han leído bien: no es un chiste de chinos ni sobran ceros). Groove termina su artículo imaginando unos Estados Unidos con un vértice de satisfechos y una inmensa base de gente con empleos mal pagados. Sin clases medias. "Yo no quiero eso para mi país", concluye. Afirmación que compartirán todos ustedes. Pero para evitar eso, nos hacen falta unos cuantos textiles.

Andy Grove, 1 de juliol de 2010

How to Make an American Job Before It's Too Late

Recently an acquaintance at the next table in a Palo Alto, California, restaurant introduced me to his companions: three young venture capitalists from China. They explained, with visible excitement, that they were touring promising companies in Silicon Valley. I’ve lived in the Valley a long time, and usually when I see how the region has become such a draw for global investments, I feel a little proud.

Not this time. I left the restaurant unsettled. Something didn’t add up. Bay Area unemployment is even higher than the 9.7 percent national average. Clearly, the great Silicon Valley innovation machine hasn’t been creating many jobs of late -- unless you are counting Asia, where American technology companies have been adding jobs like mad for years.

The underlying problem isn’t simply lower Asian costs. It’s our own misplaced faith in the power of startups to create U.S. jobs. Americans love the idea of the guys in the garage inventing something that changes the world. New York Times columnist Thomas L. Friedman recently encapsulated this view in a piece called “Start-Ups, Not Bailouts.” His argument: Let tired old companies that do commodity manufacturing die if they have to. If Washington really wants to create jobs, he wrote, it should back startups.

Mythical Moment

Friedman is wrong. Startups are a wonderful thing, but they cannot by themselves increase tech employment. Equally important is what comes after that mythical moment of creation in the garage, as technology goes from prototype to mass production. This is the phase where companies scale up. They work out design details, figure out how to make things affordably, build factories, and hire people by the thousands. Scaling is hard work but necessary to make innovation matter.

The scaling process is no longer happening in the U.S. And as long as that’s the case, plowing capital into young companies that build their factories elsewhere will continue to yield a bad return in terms of American jobs.

Scaling used to work well in Silicon Valley. Entrepreneurs came up with an invention. Investors gave them money to build their business. If the founders and their investors were lucky, the company grew and had an initial public offering, which brought in money that financed further growth.

Intel Startup

I am fortunate to have lived through one such example. In 1968, two well-known technologists and their investor friends anted up $3 million to start Intel Corp., making memory chips for the computer industry. From the beginning, we had to figure out how to make our chips in volume. We had to build factories; hire, train and retain employees; establish relationships with suppliers; and sort out a million other things before Intel could become a billion-dollar company. Three years later, it went public and grew to be one of the biggest technology companies in the world. By 1980, which was 10 years after our IPO, about 13,000 people worked for Intel in the U.S.

Not far from Intel’s headquarters in Santa Clara, California, other companies developed. Tandem Computers Inc. went through a similar process, then Sun Microsystems Inc., Cisco Systems Inc., Netscape Communications Corp., and on and on. Some companies died along the way or were absorbed by others, but each survivor added to the complex technological ecosystem that came to be called Silicon Valley.

As time passed, wages and health-care costs rose in the U.S., and China opened up. American companies discovered they could have their manufacturing and even their engineering done cheaper overseas. When they did so, margins improved. Management was happy, and so were stockholders. Growth continued, even more profitably. But the job machine began sputtering.

U.S. Versus China

Today, manufacturing employment in the U.S. computer industry is about 166,000 -- lower than it was before the first personal computer, the MITS Altair 2800, was assembled in 1975. Meanwhile, a very effective computer-manufacturing industry has emerged in Asia, employing about 1.5 million workers -- factory employees, engineers and managers.

The largest of these companies is Hon Hai Precision Industry Co., also known as Foxconn. The company has grown at an astounding rate, first in Taiwan and later in China. Its revenue last year was $62 billion, larger than Apple Inc., Microsoft Corp., Dell Inc. or Intel. Foxconn employs more than 800,000 people, more than the combined worldwide head count of Apple, Dell, Microsoft, Hewlett-Packard Co., Intel and Sony Corp.

10-to-1 Ratio

Until a recent spate of suicides at Foxconn’s giant factory complex in Shenzhen, China, few Americans had heard of the company. But most know the products it makes: computers for Dell and HP, Nokia Oyj cell phones, Microsoft Xbox 360 consoles, Intel motherboards, and countless other familiar gadgets. Some 250,000 Foxconn employees in southern China produce Apple’s products. Apple, meanwhile, has about 25,000 employees in the U.S. -- that means for every Apple worker in the U.S. there are 10 people in China working on iMacs, iPods and iPhones. The same roughly 10-to-1 relationship holds for Dell, disk-drive maker Seagate Technology, and other U.S. tech companies.

You could say, as many do, that shipping jobs overseas is no big deal because the high-value work -- and much of the profits -- remain in the U.S. That may well be so. But what kind of a society are we going to have if it consists of highly paid people doing high-value-added work -- and masses of unemployed?

Since the early days of Silicon Valley, the money invested in companies has increased dramatically, only to produce fewer jobs. Simply put, the U.S. has become wildly inefficient at creating American tech jobs. We may be less aware of this growing inefficiency, however, because our history of creating jobs over the past few decades has been spectacular -- masking our greater and greater spending to create each position.

Tragic Mistake

Should we wait and not act on the basis of early indicators? I think that would be a tragic mistake because the only chance we have to reverse the deterioration is if we act early and decisively.

Already the decline has been marked. It may be measured by way of a simple calculation: an estimate of the employment cost- effectiveness of a company. First, take the initial investment plus the investment during a company’s IPO. Then divide that by the number of employees working in that company 10 years later. For Intel, this worked out to be about $650 per job -- $3,600 adjusted for inflation. National Semiconductor Corp., another chip company, was even more efficient at $2,000 per job.

Making the same calculations for a number of Silicon Valley companies shows that the cost of creating U.S. jobs grew from a few thousand dollars per position in the early years to $100,000 today. The obvious reason: Companies simply hire fewer employees as more work is done by outside contractors, usually in Asia.

Alternative Energy

The job-machine breakdown isn’t just in computers. Consider alternative energy, an emerging industry where there is plenty of innovation. Photovoltaics, for example, are a U.S. invention. Their use in home-energy applications was also pioneered by the U.S.

Last year, I decided to do my bit for energy conservation and set out to equip my house with solar power. My wife and I talked with four local solar firms. As part of our due diligence, I checked where they get their photovoltaic panels -- the key part of the system. All the panels they use come from China. A Silicon Valley company sells equipment used to manufacture photo-active films. They ship close to 10 times more machines to China than to manufacturers in the U.S., and this gap is growing. Not surprisingly, U.S. employment in the making of photovoltaic films and panels is perhaps 10,000 -- just a few percent of estimated worldwide employment.

Advanced Batteries

There’s more at stake than exported jobs. With some technologies, both scaling and innovation take place overseas. Such is the case with advanced batteries. It has taken years and many false starts, but finally we are about to witness mass- produced electric cars and trucks. They all rely on lithium-ion batteries. What microprocessors are to computing, batteries are to electric vehicles. Unlike with microprocessors, the U.S. share of lithium-ion battery production is tiny.

That’s a problem. A new industry needs an effective ecosystem in which technology knowhow accumulates, experience builds on experience, and close relationships develop between supplier and customer. The U.S. lost its lead in batteries 30 years ago when it stopped making consumer-electronics devices. Whoever made batteries then gained the exposure and relationships needed to learn to supply batteries for the more demanding laptop PC market, and after that, for the even more demanding automobile market. U.S. companies didn’t participate in the first phase and consequently weren’t in the running for all that followed. I doubt they will ever catch up.

Job Creation

Scaling isn’t easy. The investments required are much higher than in the invention phase. And funds need to be committed early, when not much is known about the potential market. Another example from Intel: The investment to build a silicon manufacturing plant in the 1970s was a few million dollars. By the early 1990s, the cost of the factories that would be able to produce the new Pentium chips in volume rose to several billion dollars. The decision to build these plants needed to be made years before we knew whether the Pentium chip would work or whether the market would be interested in it.

Lessons we learned from previous missteps helped us. Years earlier, when Intel’s business consisted of making memory chips, we hesitated to add manufacturing capacity, not being sure about the market demand in years to come. Our Japanese competitors didn’t hesitate: They built the plants. When the demand for memory chips exploded, the Japanese roared into the U.S. market and Intel began its descent as a memory-chip supplier.

Intel Experience

Though steeled by that experience, I remember how afraid I was as I asked the Intel directors for authorization to spend billions of dollars for factories to make a product that didn’t exist at the time for a market we couldn’t size. Fortunately, they gave their OK even as they gulped. The bet paid off.

My point isn’t that Intel was brilliant. The company was founded at a time when it was easier to scale domestically. For one thing, China wasn’t yet open for business. More importantly, the U.S. hadn’t yet forgotten that scaling was crucial to its economic future.

How could the U.S. have forgotten? I believe the answer has to do with a general undervaluing of manufacturing -- the idea that as long as “knowledge work” stays in the U.S., it doesn’t matter what happens to factory jobs. It’s not just newspaper commentators who spread this idea.

Offshore Production

Consider this passage by Princeton University economist Alan S. Blinder: “The TV manufacturing industry really started here, and at one point employed many workers. But as TV sets became ‘just a commodity,’ their production moved offshore to locations with much lower wages. And nowadays the number of television sets manufactured in the U.S. is zero. A failure? No, a success.”

I disagree. Not only did we lose an untold number of jobs, we broke the chain of experience that is so important in technological evolution. As happened with batteries, abandoning today’s “commodity” manufacturing can lock you out of tomorrow’s emerging industry.

Our fundamental economic beliefs, which we have elevated from a conviction based on observation to an unquestioned truism, is that the free market is the best economic system -- the freer, the better. Our generation has seen the decisive victory of free-market principles over planned economies. So we stick with this belief, largely oblivious to emerging evidence that while free markets beat planned economies, there may be room for a modification that is even better.

No. 1 Objective

Such evidence stares at us from the performance of several Asian countries in the past few decades. These countries seem to understand that job creation must be the No. 1 objective of state economic policy. The government plays a strategic role in setting the priorities and arraying the forces and organization necessary to achieve this goal.

The rapid development of the Asian economies provides numerous illustrations. In a thorough study of the industrial development of East Asia, Robert Wade of the London School of Economics found that these economies turned in precedent- shattering economic performances over the 1970s and 1980s in large part because of the effective involvement of the government in targeting the growth of manufacturing industries.

Consider the “Golden Projects,” a series of digital initiatives driven by the Chinese government in the late 1980s and 1990s. Beijing was convinced of the importance of electronic networks -- used for transactions, communications and coordination -- in enabling job creation, particularly in the less developed parts of the country. Consequently, the Golden Projects enjoyed priority funding. In time, they contributed to the rapid development of China’s information infrastructure and the country’s economic growth.

Job-Centric Economy

How do we turn such Asian experience into intelligent action here and now? Long term, we need a job-centric economic theory -- and job-centric political leadership -- to guide our plans and actions. In the meantime, consider some basic thoughts from a onetime factory guy.

Silicon Valley is a community with a strong tradition of engineering, and engineers are a peculiar breed. They are eager to solve whatever problems they encounter. If profit margins are the problem, we go to work on margins, with exquisite focus. Each company, ruggedly individualistic, does its best to expand efficiently and improve its own profitability. However, our pursuit of our individual businesses, which often involves transferring manufacturing and a great deal of engineering out of the country, has hindered our ability to bring innovations to scale at home. Without scaling, we don’t just lose jobs -- we lose our hold on new technologies. Losing the ability to scale will ultimately damage our capacity to innovate.

Blade Didn’t Drop

The story comes to mind of an engineer who was to be executed by guillotine. The guillotine was stuck, and custom required that if the blade didn’t drop, the condemned man was set free. Before this could happen, the engineer pointed with excitement to a rusty pulley, and told the executioner to apply some oil there. Off went his head.

We got to our current state as a consequence of many of us taking actions focused on our own companies’ next milestones. An example: Five years ago, a friend joined a large VC firm as a partner. His responsibility was to make sure that all the startups they funded had a “China strategy,” meaning a plan to move what jobs they could to China. He was going around with an oil can, applying drops to the guillotine in case it was stuck. We should put away our oil cans. VCs should have a partner in charge of every startup’s “U.S. strategy.”

Financial Incentives

The first task is to rebuild our industrial commons. We should develop a system of financial incentives: Levy an extra tax on the product of offshored labor. (If the result is a trade war, treat it like other wars -- fight to win.) Keep that money separate. Deposit it in the coffers of what we might call the Scaling Bank of the U.S. and make these sums available to companies that will scale their American operations. Such a system would be a daily reminder that while pursuing our company goals, all of us in business have a responsibility to maintain the industrial base on which we depend and the society whose adaptability -- and stability -- we may have taken for granted.

I fled Hungary as a young man in 1956 to come to the U.S. Growing up in the Soviet bloc, I witnessed first-hand the perils of both government overreach and a stratified population. Most Americans probably aren’t aware that there was a time in this country when tanks and cavalry were massed on Pennsylvania Avenue to chase away the unemployed. It was 1932; thousands of jobless veterans were demonstrating outside the White House. Soldiers with fixed bayonets and live ammunition moved in on them, and herded them away from the White House. In America! Unemployment is corrosive. If what I’m suggesting sounds protectionist, so be it.

Choice Is Simple

Every day, that Palo Alto restaurant where I met the Chinese venture capitalists is full of technology executives and entrepreneurs. Many of them are my friends. I understand the technological challenges they face, along with the financial pressure they are under from directors and shareholders. Can we expect them to take on yet another assignment, to work on behalf of a loosely defined community of companies, employees, and employees yet to be hired? To do so is undoubtedly naive. Yet the imperative for change is real and the choice is simple. If we want to remain a leading economy, we change on our own, or change will continue to be forced upon us.

(Andy Grove, senior adviser to Intel, was the company’s chief executive officer or chairman from 1987 until 2005. The opinions expressed, featured in the July 5 issue of Bloomberg Businessweek, are his own.)


Un futuro de balones

Article d'Antoni Puigverd publicat a La Vanguardia el 21 d'agost de 2010

No hi ha millor manera d'expressar el conflicte amb el que es troba ara la cultura de l'esforç el món de l'educació. En comparteixo plenament les idees.


No és una illa per a joves

Publicat a La Vanguardia el 10 d'agost de 2010

M'ha agradat aquest article. Explica la història de l'illa escocesa de Lismore, ara pràcticament abandonada, on hi viuen poc més de 100 persones, la gran majoria de més de 60 anys. I no volen ni sentir a parlar de "la civilització". A més, gairebé tots els homes es diuen Duncan, el que provoca que s'hagin d'identificar pel sobrenom: "Duncan el de la granja de la muntanya", "Duncan el que va néixer el dia de Nadal"...

Estudis sobre els preus i el grau de satisfacció dels supermercats

Extret d'El 9 Nou del 13 d'agost de 2010

Últimament s'han publicat dos estudis que avaluen els supermercats. Un, fet pel departament d'Economia de la Generalitat, es fixa en els preus, i sobre un promig de 100 elabora els preus mitjans de cada supermercat. L'altre, fet per l'OCU (Organització de Consumidors i Usuaris) avalua diversos paràmetres obtenint un índex de satisfacció general per cada supermercat. Els resultats els podeu veure en el gràfic.


Quin és el número més gran que podem escriure?

Dedicat a l'Adrià Gascon.
Extret de http://www.scottaaronson.com/writings/bignumbers.html

Imaginem que participem en un concurs on, en 15 segons, hem d'escriure el número més gran que coneguem (un nombre concret, no s'hi val escriure "infinit"). Quins nombres podem escriure?

La primera idea que ens ve al cap és escriure una seqüència de nous:

Però de seguida ens n'adomem que, si en comptes d'escriure nous escrivim uns, anem molt més ràpid i podem escriure moltes més xifres en el mateix temps:

I si exponenciem? Quin número és més gran: (9^9)^9 o 9^(9^9)? El segon, així que una nova proposta és el número
que s'abrevia com

Hi ha operacions més poderoses que l'exponencial? Sí, de fet l'operació exponencial forma part d'una cadena d'operacions, anomenada la seqüència d'hiperoperacions.
La hiperoperació elemental consisteix en sumar 1:
H0(a,b) = b + 1

La hiperoperació primera consisteix en sumar:
H1(a,b) = a + b

La segona és la multiplicació:
H2(a,b) = a * b

La tercera és l'exponenciació:
H3(a,b) = a ^ b

La quarta s'anomena tetració, i es defineix com:
H4(a,b) = a ^ a ^ a ^ ... ^ a (b vegades)

La fórmula general d'una hiperoperació és:
Hn(a,b) = b + 1 si n = 0
Hn(a,b) = a si n = 1, b = 0
Hn(a,b) = 0 si n = 2, b = 0
Hn(a,b) = 1 si n >= 3, b = 0
Hn(a,b) = Hn-1(a,Hn(a,b-1)) altrament

Així, pel cas de la tetració, tenim el que havíem comentat:
H4(a,b) = H3(a,H4(a,b-1)) = H3(a,H3(a,H4(a,b-2))) = ... = a ^ (a ^ ... ^ a)

Si fixem els valors de a i b al subíndex de la hiperoperació obtenim (una versió de) la seqüència d'Ackermann. Els seus primers elements en són:
A(1) = 1 + 1
A(2) = 2 * 2
A(3) = 3 ^ 3
A(4) = 4 ^ 4 ^ 4 ^ 4

i la fórmula general és:
A(n) = Hn(n,n)

que podem calcular amb la recurrència que hem presentat abans.

Una bona resposta a la pregunta que plantegem en aquest escrit és, doncs, un número ben gran de la seqüència d'Ackermann.

La funció d'Ackermann, és a dir, la funció que donat n computa A(n) té propietats que la fan especial. És una funció computable total que no és primitiva recursiva. És a dir, existeix un algorisme (un programa) que la pot computar, però que creix més ràpid que les funcions primitives recursives. Per aquest escrit en tenim prou quedant-nos amb aquesta idea, no ho detallarem més. La funció d'Ackermann mostra que, tot i que totes les funcions primitives recursives són computables, el recíproc no és cert.

Però encara hi ha nombres més grans que els de la seqüència d'Ackermann. Però necessitem utilitzar la definició de Màquina de Turing. Una funció és computable si existeix una Màquina de Turing que la calcula en un nombre finit de passos. I podem classificar les Màquines de Turing segons el nombre de regles que tenen escrites a la cinta. Llavors, fixat un nombre N de regles, hi ha un nombre finit de MT que tenen N regles, i es divideixen en dos conjunts: les que no s'aturen i les que s'aturen. D'aquestes últimes, cadascuna executarà un nombre de passos fins aturar-se. Doncs la seqüència "Busy Beaver" es defineix com:
BB(N) = max{nombre de passos abans d'aturar-se d'una MT amb N regles}

Aquests nombres són immensos: de fet se'n coneixen ben pocs:
BB(1) = 1
BB(2) = 6
BB(3) = 21
BB(4) = 107

No es coneix el valor de BB(5), tot i que se sap que és més gran de 47 milions. I pel que fa al valor de BB(6), es coneix que supera els 8.000 bilions...

Què us sembla si responem la pregunta inicial amb un nombre ben gran de la seqüència BB?