So, the good news this year was that the President and Congress were working from the same set of numbers for the first time in a long time. The bad news is that those numbers are pretty underwhelming. The President introduced his FY15 budget request today, a budget that would remain largely flat — increasing discretionary spending just $2 billion over FY14 ($1.014 trillion in FY15 vs. $1.012 trillion in FY14). NSF would grow just 1 percent (to $7.3 billion) under the “base budget” in the President’s plan. Research at NSF would actually decrease $3 million under the President’s plan ($5.191 billion in FY14 vs. $5.188 billion in FY15). (We’ll have lots more information about NSF’s budget request next Monday when the agency rolls out its detailed budget justification.)

Recognizing that the agreed-to budget caps were overly constraining for all the Administration’s priorities, the President included a $52 billion “wish list” of additional funding proposals — called the “Opportunity, Growth, and Security Initiative” — that includes increased funding for key science agencies that could be offset by cuts to farm subsidy programs, tax increases on “multi-million dollar retirement accounts,” and other spending cuts and tax increases identified by the Administration. Were that wish list to be approved by Congress, NSF could see an additional $552 million in funding (and R&D agencies overall would see an increase of $5.3 billion) However, congressional Republicans have already declared the wish list DOA.

Funding for other agencies in the President’s base budget is a bit of a mixed bag:

  • DOE basic and applied research would be up 6.1 percent in the President’s plan ($8.412 billion in FY 15 vs. $7.932 billion in FY14)
  • DOD basic and applied research would see an increase of 4.4 percent ($6.582 billion vs. $6.307 billion
  • NIST basic and applied research would increase 3.3 percent ($598 million vs $579 million)
  • NIH basic and applied research would increase 0.7 percent ($29.403 billion vs. $29.205 billion)
  • Homeland Security basic and applied research would decrease 1 percent ($250 million vs. $251 million).

Keep in mind that the expected inflation rate between FY 2014 and FY 2015 is about 2 percent.

The White House has released an R&D Budget Fact sheet that goes into some of the details.

But we’ll learn more about the agency priorities as the agencies roll out their own budget request over the next week or so.

As always, we’ll have the details as we learn them!

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House Budget Chair Paul Ryan (R-WI) and Senate Budget Chair Patty Murray (D-WA) announced Tuesday afternoon that they’d reached an agreement on FY 2014 and FY 2015 budget numbers that would avert sequester levels by providing about $63 billion of cap relief over both years. That sequester relief includes $22 billion for non-defense discretionary spending in FY 2014 and $19 billion in FY 2015, meaning that appropriators will have some additional room to provide funding for federal science agencies like NSF, NIH, NIST and DOE, should they choose to.

The agreement, assuming it’s adopted by both chambers (not a slam dunk, but a decent bet), would avert a shutdown in January and allow appropriators to move forward with an omnibus appropriations bill for most of the outstanding FY14 appropriations, something they have indicated they’ll do with 12 of the 14 bills in the second week of January. Maybe more importantly, the agreement sets the caps for FY15 as well, allowing appropriators to begin work on FY15 bills on schedule, knowing the House and Senate are working from the same set of numbers for the first time in many years, and with a reasonable expectation that they might actually get some of the bills done in regular order — something they haven’t done in, well, probably a decade or more.

There’s enough to hate in the agreement for both parties, which is a pretty good indication that it’s a decent compromise, and leadership on both sides believes they have the votes to pass it. Both Ryan and Murray spoke about the agreement as being an essential piece of Congress reasserting its power of the purse, something it had abdicated to the Administration with the sequester deal (where the Administration got to make the decisions about how the cuts fell on programs at agencies), and both emphasized that it was an important step in changing the crisis-to-crisis mode of legislating that Congress has adopted of late. Let’s hope that’s true on both counts.

Anyway, some good news about budget after many, many months/years of frustrating developments. We’re nowhere near out of the brutal budget climate that has pervaded for the last few years, but perhaps there’s a small bit of sanity that’s beginning to emerge. If so, we’ll have all the details!

The committee has released the text of the agreement, a section by section summary, and an overall summary. The House could vote by the end of the week, with Senate action shortly thereafter.

On Tuesday, June 18th, IBM Research hosted a presentation and panel discussion on the Hill with House Representatives on cognitive computing. According to IBM Research, cognitive computing systems include “systems that learn and interact naturally with people to extend what either man or machine could do on their own.” Essentially, these systems help human experts make better decisions by allowing them to better sift through big data. Cognitive computing systems, or supercomputers, are not programmed to perform functions; rather, “they use artificial intelligence (AI) and machine learning algorithms to sense, predict and, in some ways, think.” These systems can draw their own insight from big data. The goal is not necessarily to be the expert, but rather to better aid the human expert by penetrating big data they otherwise cannot.

IBM Research Vice President David McQueeney demonstrated the power of supercomputing through a weather cleanup example. Trees have very predictable growth patterns, and supercomputers can easily sift through tree data in a given location. If a powerful storm such as Hurricane Sandy were to damage an area, for instance, cognitive computing systems could help cities predict which areas will need crews to rebuild power lines based on the tree data. These systems could save millions of dollars for cities. Currently, IBM’s own supercomputer IBM Watson can sift through 1.5 million patient records and give doctors treatment options in seconds (see the power of the IBM Watson below).

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