Conservation could eliminate the need to drill for any oil in the Gulf of Mexico.

The U.S. consumes about an almost unimaginable amount of oil every day: 20,680,000 barrels of oil per day (and see here). Keep in mind that each barrel contains 42 gallons. Thus, Americans currently use 20,680,000 barrels per day = 239 barrels per second = 10,000 gallons of oil per second.Therefore , we desperately need to maintain almost 4,000 drilling platforms in the Gulf of Mexico in order to keep drilling for oil, right? Not so fast. Why aren’t we seriously discussing our ability to entirely eliminate offshore drilling by getting just a little bit serious about conservation? Consider the following statistics, which should be on the front page of every newspaper in the United States because [caption id="attachment_12529" align="alignright" width="210" caption="Image: creative commons"]Image: creative commons[/caption] they prove that we don't need offshore drilling but that we do need to seriously implement conservation measures for many reasons (one of which is impending peak oil):

Projecting ahead to the year 2016, the total oil production from the Gulf of Mexico will never exceed 2.1 million barrels of oil per day. Within the next 10 years, total GOM oil production is expected to exceed 1.7 million barrels of oil per day (MMBOPD), a projection based on existing shallow and deepwater operator commitments as shown in Table 2 and Figure 2. If industry-announced discoveries and undiscovered resources realize their full potential, production could reach 2.1 MMBOPD.

This information comes from page 12 of “Gulf of Mexico Oil and Gas Production Forecast: 2007-2016,” published by the U.S. Department of the Interior. See also, this chart, Figure 2 on page 14 of this same report:

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How are Humans Better?

A new comment thread on an old post discusses the precept that humans are somehow "better" than all other creatures. Sure, as a member of our team, I'd like to think that we are Number One. We've even written books attributed to deities that prove that we are the reason for creation, that the octillions of stars in the universe were all put there just for our amusement. Therefore, the book and its believers maintain, we must be the best thing ever. But as an educated human raised by scientists to find first sources and question suppositions, I wonder: "How are we better?" I have posted before on some of the ways in which our Creator (to use that paradigm) has short changed us. Name any characteristic of which we are proud, and it is easy to find another creature that exceeds our ability. I can only think of one exception: Communicating in persistent symbols. Unlike cetaceans, birds, fellow primates, and others who communicate fairly precisely with sounds, gestures, or chemical signals, we can detach communication from ourselves and transport or even delay it via layers of uncomprehending media (paper, wires, illiterate couriers, etc). We can create physical objects that abstract ideas from one individual and allow the idea to be absorbed by another individual at a later time. It also allows widely separated groups to share a single culture, at least in part. This learned behavior is based on our apparently unique ability to abstract in multiple layers and to abstract to a time well beyond the immediate future. We can take an idea to a series of sounds to a series of static symbols, and back again. Our relatively modern ability to reason abstractly (math, science) evolved from our ability to abstract communications. Even Einstein couldn't hold the proof of E=MC2 in his head. But is this unique ability really sufficient to declare ourselves overall inherently "better"?

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Biology is drowning in data and complexity

In the April 2010 edition of Nature (available only to subscribers online), you can read a counter-intuitive story of illustrating that more information is sometimes add confusion, rather than making things simpler. Maybe another way of putting it is that the path to understanding can often take one through phases of disorientation resulting from new influx of accurate data. This particular story, by Erika Check Hayden, titled "Life Is Complicated," considers what has happened in the field of biology subsequent to the Human Genome Project. Prior to the Project, many biologists guessed that the human genome contained about 100,000 genes that coded for proteins. At the conclusion of the project, however, we found out that only about 21,000 human genes code for proteins. One might think that this would simplify the field of biology, especially since biologists now know what many of these genes are. Many people thought that we were going to have for ourselves a clearly understandable "blueprint," of the human species. The opposite is happening, however: "It opened the door to a vast labyrinth of new questions." What kinds of questions? This article really surprised me with the vast scope of new territory opened up by the Human Genome Project. It can be summed up by Hayden's quote from biochemist Jennifer Doudna: "The more we know, the more we realize there is to know." Hayden explains that sequencing the genome undermined "the primacy of genes by unveiling a whole new classes of elements--sequences that make RNA or have a regulatory role without coding for proteins." It turns out that "much non-coding DNA has a regulatory role "that we are just beginning to understand." To illustrate how complex things have gotten, Hayden discusses what we've now learned about a single protein, "p53," which for many years was simply known as a tumor suppressor protein. Consider what we know now: In 1990, several labs found that p53 binds strictly to DNA to control transcription, supporting the traditional Jacob-Monod model of gene regulation. But as researchers broadened their understanding of gene regulation, they found more facets to p53 . . . [R]esearchers now know that p53 binds to thousands of sites in DNA, and some of the sites are thousands of base pairs away from any genes. It influences cell growth, death and structure and DNA repair. It also binds to numerous other proteins, which can modify its activity, and these protein-protein interactions can be tuned by the addition of chemical modifiers such as phosphates and methyl groups to create through a process known as alternative splicing. P53 can take nine different forms, each of which has its own activities and chemical modifiers. Biologists are now realizing that p53 is also involved in processes beyond cancer, such as fertility and very early embryonic development. In fact, it seems willfully ignorant to try to understand p53 on its own. Instead, biologists have shifted to studying the p53 network as depicted in cartoons containing boxes, circles and arrows meant to symbolize its maze of interactions. Hayden reminds us that the p53 story is one of many similar stories in post genomic-era biology. She explains that we now know that many of the signaling pathways that we thought we were close to understanding are not simple and linear but organized in vast complex networks that sometimes appear fractal. She quotes James Collins, a bio-engineer: "Kevin made the mistake of equating the gathering of information with a corresponding increase in insight and understanding." Here's another counter-intuitive result of this new dilution of information: many of our models have gotten too complex to be useful. In many cases the models themselves quickly become so complex that they are unlikely to reveal insights about the system, degenerating instead into mazes of interactions that are simply exercises in cataloging. The genome project has made biologists into kids in a big candy store: a candy store with unending aisles and endlessly deep bins of dazzling, disorienting candy, much of which is currently out of our reach. Such is the horizon of new knowledge, equal parts frustrating and tantalizing.

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The state of robotics

In a recent article in Discover Magazine called "Machine Dreams," (May, 2010, not yet available online) a panel of robotics experts discussed the relationships among people and the machines we call robots. What is a "robot"? Rodney Brooks of MIT offered this definition:

[A] robot is something that senses the world, doesn't some sort of competition, and decides to take an action outside of its physical extremity. That action might be moving around, or it might be grabbing something and moving it. I say "outside it's extremity" because I don't like to let dishwashers be defined as robots.

The panel offered a lively discussion, focusing on many real-world applications. Robots are doing many things these days, including surveillance and reconnaissance during flood disasters. Robots are already quite good at some things, but Rodney Brooks offers some sobering thoughts for those who think of robots as replacements for human beings. We have quite a ways to go. Where are we headed? Here are the goals for which robotics researchers are currently striving to reach (according to Brooks):

First the object recognition capabilities of a two-year-old child. You can show a two-year-old a chair that he's never seen before, and he'll be able to say, "that's a chair." Our computer vision systems are not that good. But if our robots did have that capability, would be able to do a lot more.

Second, the language capabilities of a four-year-old child. When you talk to a four-year-old, you hardly have to dumb down your grammar at all. That is much better than our current speech systems can do.

Third, the manual dexterity of a six-year-old child. A six-year-old can tie his shoelaces. A six-year-old can do every operation that a Chinese worker does in the factory. That level of dexterity, which would require a combination of new sorts of sensors, new sorts of actuators, and new algorithms, will let our robots do a lot more in the world.

Fourth, the social understanding of an eight or nine-year-old child. Eight or nine-year-olds understand the difference between their knowledge of the world and the knowledge of someone they are interacting with. When showing a robot how to do a task, they know to look at where the eyes of the robot were looking. They also know how to take social cues from the robot.

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